personal statement on data analytics

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• Data Science Masters Personal Statement Sample

Written by Ben Taylor

This is an example personal statement for a Masters degree application in Data Science. See our guide for advice on writing your own postgraduate personal statement .

The emergence of big data over the past decade as a power for good – and, dare I say it, evil – has convinced me of the importance of developing and honing my skills in this arena. I’m keen to ‘future-proof’ my career and I believe that your MSc Data Science degree is the programme to help me achieve my goals.

Although I don’t come from a traditional STEM background, having studied a Bachelors degree in Linguistics, the professional experience I’ve gained since graduating has given me a solid foundation in the principles associated with data analytics. I’ve worked for two years as an SEO and PPC Executive for a major e-commerce agency, helping to provide insight into website traffic trends and advert effectiveness, and suggesting ways to boost online performance. I’ve used tools like Semrush and Moz, as well as Google Analytics and Search Console, and crave the opportunity to delve even deeper into the world of data outside of an e-commerce agency.

The potential applications of machine learning and natural language processing are particularly fascinating to me. I’ve watched with interest the arrival of deep learning software that purports to generate unique content based on user prompts. Although the end-product of these programmes is sometimes crude, I think they’re incredibly promising.

The coronavirus pandemic has also shown the value of big data in a healthcare setting, with large-scale modelling a vital source of information and guidance for policy-makers across the globe. The pandemic has also illustrated the importance of presenting this data in a clear and responsible manner and I’ve been impressed by the development of the UK’s own coronavirus statistics dashboard, which I think should be seen as a benchmark standard.

I think that your conversion course is perfectly tailored for my skillset, as someone with an amateur, self-taught background in coding (including the basics of Python). I’m looking for a rigorous degree that will challenge me and ultimately equip me with the knowledge to make a meaningful contribution in the private or public sector in the coming years. I hope to apply my new-found expertise in a company with a start-up culture, perhaps in the fin-tech sector where algorithmic know-how is in high demand.

What are some of my options for studying a Masters in Data Science?

Msc - data science and marketing, goldsmiths, university of london department of computing, master in business analytics & data science, eu business school (munich campus) mba programs - munich campus, eu business school (geneva campus) mba programs - geneva campus, impact msc in data science for sustainable development, tomorrow university master programmes, management & data science (m.sc.), leuphana university lüneburg graduate school, our postgrad newsletter shares courses, funding news, stories and advice, find a masters in data science.

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Ben worked in the FindAMasters content team from 2017 to 2022, starting as an Assistant Content Writer and leaving as Student Content Manager. He focused on producing well-researched advice across a range of topics related to postgraduate study. Ben has a Bachelors degree in English Literature from the University of Sheffield and a Masters from the University of Amsterdam. Having also spent a semester at the University of Helsinki through the Erasmus programme, he’s no stranger to study abroad (or cold weather!).

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• Data Science

Data Science Personal Statement in 2024 [Sample & Examples]

Home Blog Data Science Data Science Personal Statement in 2024 [Sample & Examples]

Data science is one of the most popular career options for students, especially those pursuing a Bachelor's degree. It is also one of the most sought-after courses in universities today. If you just want some ideas on how to write a data science personal statement, then this article is for you. Also, if you’re someone who is willing to secure a career in the field of data science, then it is recommended that you pursue Data Science Courses that will enable you to learn all aspects and principles of data science. 

What is a Data Science Personal Statement?

In a nutshell, the personal statement for data science is a document that you write to explain why you are interested in pursuing the subject and what you can bring to the table. It should be written in a way that shows your interest in the subject and why you want to study it. You may want to include information about the following in your data science personal statement.  

• What led up to your decision to pursue this field? 
• Why do data scientists matter? What problems need solving by them? What value do they provide society as well as individuals? 
• How will studying this specific field help prepare you for future careers or additional educational opportunities (e-learning programs, etc.)?

You can also include the following:  

• What are your goals for this degree?  
• How will it benefit you?  
• What do you hope to achieve from studying data science?  
• Why is this field important in today’s society?  
• What are the challenges that you see in this field?  
• How will you address those challenges?  
• What do you think the future of data science is?  
• How do you plan on staying relevant as technologies and trends change?

The Importance of Creating a Data Science Personal Statement

Data science personal statement is a formal document that will be used by the company to evaluate your skills. If you are applying for a Data Science job and want to impress the hiring manager, then you must write a strong data science personal statement.

A good personal statement for a master's in data science must be unique, creative, informative and interesting to read. It should describe not only your skills and experience but also showcase your ability to think critically and creatively.

A well-written data science personal statement will help you stand out from other applicants and make yourself an ideal candidate for the job that you want. Here are some useful tips for writing a strong data science personal statement: 

• Be honest and straightforward in your personal statement. 
• Don’t exaggerate or lie about your skills, experience and achievements. If you don’t have any relevant work experience, then focus on other areas where you can showcase your skills, such as volunteering or community projects. 
• Know the company that you are applying to and tailor your personal statement accordingly. A generic resume won’t help if you are applying for a specific job position. Instead, write a customized letter that shows how well-suited you are for this role. 
• Keep it short and sweet. The best personal statements are between a few hundred to a few thousand words long. Don’t try to cram everything in one big paragraph; break it up into smaller sections that will make it easier for readers to digest. 

So now you might have understood how important data analytics personal statements are. To learn how to create a personal statement, it is recommended that you enroll in the Best Data Science Bootcamps . 

Data Science Personal Statement Sample

I am writing this Data Science Personal Statement for the MS in Data Science program at UC Berkeley. My goal is to explain why I want to pursue a career in data science and how my experience as an undergraduate student has prepared me for graduate school. As you can see from my resume, I have had many opportunities to work with large amounts of data through internships and research projects over the course of my academic career. These experiences have given me valuable insight into how large-scale computational problems can be tackled by applying statistical methods under tight deadlines while still maintaining quality control over your results. 

In addition, I have taken classes such as AI/ML Systems Design & Implementation and Machine Learning Algorithms. These classes have helped me develop new ways of approaching problems while also providing an understanding of why certain algorithms work better than others when applied in specific situations. 

I am a Data Science Major at UC Berkeley and have been for two years. In order to graduate with a major in Data Science, you must complete four required classes, one of which is an independent study project. 

I have chosen to take this independent study project in order to gain hands-on experience with a data science problem of my choosing and to learn how to effectively apply machine learning algorithms in the real world. My goal is to create an application that can accurately predict where students need tutoring based on their past grades. This project will require me to use various classes of statistical models, such as regression, decision trees, and neural networks. 

How to Write a Personal Statement for Masters Programme in Data Science?

If you are looking for the best way to write a sample personal statement for a master in data science, you should follow these steps: 

• Step 1: The first step is to find out what courses are available in your area and how long it takes to complete them. You can find this information on websites online. 
• Step 2: Once you have this information, you need to think about how much time you will have available each day. It is important that you do not leave your studies until you finish all of your courses because once you finish your degree program, there will be no more work available for you. Your ability to continue working will depend upon how well your personal statement for data science courses was received by universities and whether or not they offer scholarships for those who want to study abroad or online. 
• Step 3: In order to write a good personal statement for M.Sc data science, you will need to think about why you want to continue your education after completing your bachelor's degree program. This could be because of what happened during college or because of something else entirely (such as family obligations). If it is something that happened during college, then you will need to explain what that event was and how it has affected your desire to continue your education. If it is something that happened outside of college, then you should talk about how that event impacted your academic performance and why you want to continue studying.

Data Science Personal Statement Example 

Following is a data science personal statement example. You can refer to this data science statement of purpose example and keep in mind the necessary points.

Source: personal-statement-examples.com

Tips to Write an Effective Data Science Personal Statement

The following tips will help you write an effective personal statement for a master in data science: 

1. Use a Template

It's best to use a template that has been created by experienced admissions officers and other professionals in the field. This means you can skip the writing process entirely since they've already done most of it for you. 

2. Keep Your Sentences Short and Simple

Your goal should be no more than one or two paragraphs per section (including your application summary), which means keeping your sentences as short as possible without compromising clarity or coherence. If there are too many adjectives or numbers used in an otherwise simple sentence, try replacing them with action verbs like "ran" instead of "ran fast." 

3. Avoid Clichés

In your data science personal statement sample, instead of saying things like "I am dynamic," try saying something more descriptive such as “I am highly dynamic” instead because this shows off how creative your mind works while also showing off how well-rounded personas are important traits needed by anyone working at companies when writing an M.Sc data science personal statement.  

Do’s and Don’ts While Writing Personal Statement

Data science is a booming field with a lot of opportunities. You can work anywhere and make a good salary with this skill. If you think that it’s not for you, then it’s time to think again. The world has changed and so have our needs as individuals. Data science professionals will be needed in the future because of their role in shaping our lives as we know them today. In order to pursue a career in this broad field of data science, it is recommended that you pursue KnowledgeHut to learn its principal aspects and gain in-depth knowledge about data science personal statement. Data Science Courses to learn its principal aspects and gain in-depth knowledge about data science.

Frequently Asked Questions (FAQs)

Find out what diploma courses are available in your area and how long it takes to complete them. Once you have this information, you need to think about how much time you will have available each day. After evaluating all these things, start writing your personal statement using templates. 

• The reason(s) why you selected this subject(s) 
• Your chosen area of study and how it relates to the current studies 
• Your experiences in relation to your chosen subject(s) 
• What are your interests and responsibilities in relation to the subject you are studying? 
• After university, what's next? 
• A summary of why you will make an excellent student 
• Don’t use quotes 
• Don’t let spelling and grammatical errors spoil your statement. 
• Don’t copy and paste 

During the writing of the letter of intent for the MS in Data Science course, it is important to take into account the basic questions asked by the institution, including what kind of ambitions the prospective candidate has and the inspiration behind those ambitions. If the students do not want to sound conversational in their essays, then they should keep in mind that the tone should be formal instead of informal.

Ashish Gulati

Ashish is a techology consultant with 13+ years of experience and specializes in Data Science, the Python ecosystem and Django, DevOps and automation. He specializes in the design and delivery of key, impactful programs.

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Data Science MSc personal statement

• Reading time: 3 minutes
• Price: Free download
• Published: 13th September 2019
• Word count: 616 words
• File format: Text

Like the vast and ever-expanding universe, the big data fields are in a perpetual expansion mode. Both fascinate me. The sheer volume and complexity of data being generated in today’s world present unprecedented opportunities for exploration and analysis. Harnessing the power of data can lead to groundbreaking discoveries, transformative insights, and innovative solutions to some of the most pressing challenges we face.

My education has provided me with a strong foundation to navigate this data-driven landscape. Through my coursework in computer science, I have gained a deep understanding of algorithms, data structures, and programming languages, all of which are crucial components in extracting meaningful information from large datasets. This knowledge has not only enabled me to work comfortably with computers and numbers but has also fostered my passion for leveraging data to uncover valuable insights.

Building on my educational foundation, my work experience in the field of technology and business management has allowed me to put theory into practice. I have had the opportunity to work on large-scale, data-intensive projects that have exposed me to the challenges faced by various industries and governments. The experience has strengthened my ability to analyze complex datasets, identify patterns, and derive actionable intelligence that can drive informed decision-making.

In this era of big data, organizations have come to realize the importance of transitioning from traditional methods to data-driven approaches. It is now essential to understand and process all aspects of data and analyze it effectively to arrive at optimal choices for decision-making. This realization has sparked a surge in demand for professionals who possess the skills and expertise to transform raw data into meaningful insights. I have been fortunate enough to develop hands-on experience with programming languages like SQL and JSON, as well as data visualization tools like Excel and Tableau. These practical experiences have allowed me to deepen my understanding of data analysis techniques and strengthen my ability to communicate complex information visually.

Furthermore, my passion for big data extends beyond technical proficiency. I am captivated by the immense potential of predictive analytics and artificial intelligence (AI). The ability to leverage advanced algorithms and machine learning models to uncover hidden patterns, forecast trends, and make data-driven predictions holds tremendous promise for addressing complex challenges across industries. By exploring these fields, I aim to contribute to the development and application of AI techniques that can empower organizations and individuals to make informed decisions and drive positive change.

As I look ahead, my goal is to be a Data Scientist and contribute to an organization’s data-driven decision-making processes. I am particularly excited about the prospect of applying my skills and knowledge to real-world scenarios, where I can utilize data to uncover insights and create innovative solutions. Ultimately, I envision establishing my own enterprise that focuses on mentoring and guiding the next generation of data scientists, fostering a community of individuals dedicated to using data for social good and addressing pressing challenges.

The MSc Data Science program with an industry placement at Essex University aligns perfectly with my aspirations. Its comprehensive curriculum and emphasis on practical application will provide me with the theoretical foundation and hands-on experience necessary to excel in the field. I am eager to immerse myself in an environment that fosters collaboration, innovation, and critical thinking, where I can learn from esteemed faculty and engage with like-minded peers.

In conclusion, my passion for big data, combined with my educational background and industry experience, fuels my desire to pursue the MSc Data Science program at Essex University. By expanding my knowledge, developing advanced analytical skills, and immersing myself in real-world applications, I am confident that I will be well-prepared to make a meaningful impact in the world of data science .

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Personal Statement that got selected to MS in Data Science, University of Pennsylvania (UPenn)

Penn’s Master of Science in Engineering (MSE) in Data Science prepares students for a wide range of data-centric careers, whether in technology and engineering, consulting, science, policy-making, or understanding patterns in literature, art or communications.

It blends leading-edge courses in core topics such as machine learning, big data analytics, and statistics, with a variety of electives and an opportunity to apply these techniques in a domain specialisation – a depth area – of choice.

So, what does it take to get into one of the top 15 programs of the USA in Data Science? I mean, look at it! Wouldn’t you want to spend 2 years here?

So, let’s look at the ‘Personal Statement’ requirements what the UPenn lists out in its Admission Requirements:

• No more than two pages in a readable font/size:
• Why are you interested in this program?
• What have you done that makes you a great candidate?
• How will you benefit from the program?
• How do you plan to contribute to the student community in SEAS while you’re here?
• Why will you succeed in the program?
• What will you do/accomplish once you have completed the program?

As it is amply clear, the AdCom doesn’t want the details of EVERYTHING that you have done in your academic projects. You should answer only these 6 questions, in a way that best justifies your interest in this program. Right?

Here is where the Mridul got it wrong.

About Mridul

Mridul grew up in Mumbai, went to KJ Somaiya College Of Engineering in Mumbai, and had a GPA of 8.46.

He had a GRE score of 322 (167 Q 155 V) and a TOEFL score of 103.

His academic projects reasonably aligned with the research work at UPenn, one of his dream schools.

When he sent us the first draft, it was his entire story of all the things he has done till now. In total, it was 4 PAGES LONG!

So, our first revision was to cut short the massive piece of self-appreciation, to a workable draft of around 1000 words.

Then, we cherry picked some of the most notable projects of Mridul, and tried to address the questions that the AdCom was really looking for.

After 3 rounds of revision, we arrived at the final draft which looked like this:

As it can be seen, each paragraph of Mridul’s Personal Statement, tries to address a question which helps the AdCom to decide if you are the ‘RIGHT FIT’ for the class.

Since there was no hard limitation on the number of words, we stuck to around 1100 words to clearly and concisely tell Mridul’s story to the AdCom.

Mridul was accepted to three graduate programs – University of Pennsylvania (MS in Data Science), University of California Irvine (MS in Computer Science), and CMU (MS in Data Science)

We couldn’t be happier! Like this happy puppy.

Read Shrishti’s application journey to MS in Computer Science, University of Southern California (USC)

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• Last updated October 7, 2021
• In Innovation in AI

How To Write An Appealing Personal Statement For Masters Programme In Data Science

Illustration by How To Write An Appealing Personal Statement For Masters Programme In Data Science

• Published on July 31, 2020
• by Sejuti Das

Besides submitting test scores, recommendation letters, and an undergraduate transcript, one essential requirement of applying to a data science masters programme is the application essay — aka personal statement. The personal statement is where applicants need to convince the professors their ability and worth of getting selected in the master programme . 

In fact, many a time, a personal statement acts as a deciding factor for getting chosen for a prestigious masters programme in the field of data science . Thus, one needs to be extremely cautious while writing a personal statement for their master’s application. Not only does it help the university authorities determine the sincere interest of the applicant to enrol for the course, but also provide a chance to the students to stand out of the crowd highlighting their skills and relevancy.

Having said that, data scientists are experts in mathematics, but writing might not always be their expertise , and a personal statement is usually longer than you think and requires to be well crafted in order to grab the attention of professors and administrators. So, if decided to pursue higher studies in the data science field and have narrowed down universities to apply, this article can help you write a winning personal statement required to apply for the data science masters’ programme.

Also Read: The 10 Most Promising Data Science Masters Programs In US

Planning Is The Key: Highlight The Reason To Study Data Science Masters

Although it is stated as ‘personal,’ a personal statement doesn’t require applicants to share the intimate details of their life; instead, it needs to highlight the intention of the applicant for the particular master’s programme. To avoid any confusion or mistakes, the first step to write a personal statement for a data science masters programme is to brainstorm around it and plan it before actually starting to write. It is critical to make notes and use bullet points when planning, which can later be referred to while writing the personal statement. One should research thoroughly about the course requirements and the university, and prepare a list of their achievements and goals that can come handy while writing the essay. 

Most universities expect their applicants to adhere to a specific word limit for the personal statement, and thus a good brainstorming will help applicants to keep their essay relevant and to the point. Planning will help in setting the context, creating a structure and forming a narrative of the piece that is critical for drafting a compelling statement.

Also Read: What Not To Include In Your Data Science Resume

Have A Killer Intro & A Concise Conclusion: Relevant To The Passion For The Field

An attention-grabbing intro and a hard-hitting conclusion are again critical for writing a compelling personal statement. The first paragraph can create the first impression of the applicant in front of the professors, and a sharp end will help them remember that candidate among the crowd. The readers of the personal statement are the experts from the data science industry and academics; thus, they expect the writeup to be extremely intriguing in terms of content. 

Personal statements are usually lengthy but require to be extremely clear in sending out the message. Rather than starting the essay with some cliches, data science applicants should begin their personal statement highlighting their passion for the stream and their domain proficiency. And to have a definite ending, these data scientists must ensure to convey their genuine interest in pursuing the master’s programme, and how their skills are relevant to the stream.

Also Read: Tips And Templates For A Data Scientist Resume

Be A Good Story Teller: Highlight Experiences & Skill Sets

Thirdly, data science applicants must showcase their skill sets and experience in their personal statements without repeating the information that is already mentioned in their application form. And that’s why it is critical to be a good storyteller with their statement, where applicants can highlight their skills by talking about a particular data science research project that helped in solving real-life problems. One can also point out their experiences, knowledge, and quantify their expertise in the field that can help them in pursuing further studies.

The job of the personal statement is to let the administrators and professors know the abilities of the applicants to be qualified for the master’s programme. Data scientists can also mention their thesis, publications, journals or any relevant activities that can help them in getting selected. A well crafted personal statement avoids clichés, jargons, and too many details, and should be presented formally with a clear narrative.

Also Read: How To Create A Compelling Cover Letter To Land A Data Science Job

Focus On Your Domain & The Programme

Unlike undergraduate courses, masters programmes are more specific as well as require applicants to understand the domain they are pursuing. Consequently, while writing a personal statement, one needs to sync their interest according to the requirement of the programme and emphasise on the specific skills that match the area of expertise. One can also network with relevant faculty members and seniors to get a better understanding of the requirements of the program.

Many universities are also working on several ongoing data science projects, citing one of them corresponding to the interest, can also be a great addition to the personal statement. Furthermore, applicants can also write about what inspired them to pursue this particular domain and how their work will contribute to the field. One can also share their personal experiences and how that has helped in pursuing this course.

Also Read: What Data Science Graduates Need To Do To Get Hired During Covid-19

Don’t Be Generic: Customise The Write Up For The Course

Lastly, it is critical that the essay is unique and thus requires to be customised according to the university and its requirements. Applicants don’t have to start from scratch every time they are applying to a university, but they must ensure that they still provide a unique draft personal statement to each application. Professors and administrators read thousands of personal statements in a day, and therefore to be unique, applicants cannot pick up generic content to build their essay.

Applicants can also make the personal statement unique by adding up personal experiences relevant to the field, which will not only make the read interesting but also will allow the readers to empathise with the applicant. One can also add up a few of their failures to make it sound genuine as well as relatable. Usually, masters programmes don’t conduct face to face interviews; thus, personal statement plays a vital role in the applicants’ admission process.

Also Read: 10 Commonly Asked Puzzles In A Data Science Interview

Other Things To Keep In Mind

• Personal statements are not university applications, so don’t be repetitive.
• Highlight why this university is the right choice for the career you are planning to pursue.
• Although it’s the life experiences one shares in their personal statements, it indeed requires to be professional and to the point. 
• Avoid grammar, spelling, and punctuation errors.

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Home / Data Science Programs / Best Master’s in Data Science Programs / Statement of Purpose

How to Write a Statement of Purpose for Master’s in Data Science

Many colleges and universities require a statement of purpose for master’s in data science student applications. The statement of purpose can play an important role in your application, as it allows admissions staff to learn about your goals, experience and education outside of scores and grades. This guide will cover what a statement of purpose is, what needs to be included in it, frequently asked questions and tips to help craft your own.

What Is a Statement of Purpose for Master’s in Data Science?

A statement of purpose is a short essay written by master’s of data science applicants discussing their work and educational history, goals for the program and future career interests. A statement of purpose for master’s in data science programs may also detail any deficiencies in an application such as an employment gap, low GRE or GMAT test scores or grades and information about independent study in lieu of other relevant coursework. The statement of purpose provides a space to highlight your specific life experiences and goals in your own words.

What Is the Admissions Committee Looking for in Your Application?

Admissions committees typically look for the following information:

• Who is applying?  What about the student’s academic or personal background, work experience or extracurricular activities stands out? Does the applicant show a history of demonstrated interest in data science? What will they be able to add to a graduate program environment?
• Does the applicant have analytical skills or experience?  Data science requires a person to deeply analyze large and complex data sets. While some core capacities, like mathematics, may be taught, a statement of purpose provides a space to demonstrate analytical skills or relevant experience.

Statement of Purpose Format Requirements

While every school has different requirements, the general format for a data science master’s statement of purpose may include:

• Length: 1-2 pages; school will specify length.
• Word Count: 250-500 words; some schools allow up to 1,000 words.
• Spacing: Double or single spaced
• Font: Times New Roman in 12-point font
• Margins: No less than 1 inch
• Format: Microsoft Word (.doc, .docx) or PDF format

Refer to the college or university’s requirements before submitting, particularly if you are sending out multiple statements of purpose to different schools.

Statement of Purpose vs. Personal Statement

Master’s in data science programs may ask for a statement of purpose or a personal statement—some may ask for both. While these might seem like the same thing, there are a few distinctions.

A statement of purpose typically is focused on academic and analytical information. A school requesting a statement of purpose may request information about reasons for applying for graduate study as well as relevant professional interests and goals. A personal statement might be a broader essay asking about life experiences and interests—though still as they relate to the program.

It’s important to read admissions requirements carefully to determine what information each school wants from either a statement of purpose or a personal statement.

10 Tips for Statement of Purpose for Data Science Programs

A statement of purpose may be daunting for master’s in data science applicants, but there are some steps you can take to make sure you’re delivering a good effort. The tips below can help guide you while writing your statements of purpose for data science programs.

Read Examples of Statements of Purpose for Data Science

Read samples of statements of purpose. If you have access to successful applicants’ essays, read them. If not, read a wide variety of statements of purpose and notice what does and does not work. Be sure not to plagiarize as it could be grounds to deny your application.

Brainstorm Topics and Decide on a Structure

As mentioned above, a statement of purpose should highlight who you are and how you work analytically. Take time to brainstorm relevant topics that showcase experience as well as signs of interest in the data science field. After you have your bullet points set, focus on a structure that best highlights you as an applicant. Make an outline before you start writing.

Pick One or Two Narrow Topics and Stay Focused

A statement of purpose should be clear and to the point. It’s not a recap of your entire life or resume. Avoid covering too much information in your statement of purpose. Stay focused on one or two key topics and provide plenty of supporting information to showcase your analytical skills as it relates to those points.

Make Your First Paragraph Interesting

Admissions committees read hundreds of applications. A focused and interesting introductory paragraph can grab the attention of the reader and keep them from putting your statement down. A personal anecdote, a thought-provoking question or an emotionally compelling story at the beginning of your statement of purpose can all grab a reader’s attention.

Highlight Information That Sets You Apart

Write about any activity that highlights your strengths as a data scientist. If you have relevant experience on a resume or affiliations with a professional organization, make sure you highlight that. A statement of purpose, in part, is about what makes you qualified to  become a data scientist .

Keep the Focus on YOU

A statement of purpose is about how your experience, culture and background has helped prepare you for a career in data science. This is not the time to write at length about your professor’s career or general concepts of data science. A statement of purpose often requires a limited amount of space. Make sure you are using it effectively to highlight your own strengths.

Be Yourself and Don’t Fake Experience

Take the truthful approach and recall your experiences and accomplishments with complete honesty and authenticity. While it may be tempting to inflate your experience or accomplishments in data science or analysis, misrepresenting data—or outright lying—will hurt more than it will help.

Keep Language Concise and Tone Positive

Data science is used to draw information from raw data sets and as such, those working in data science may need to be able to explain their findings. A statement of purpose is the first place you can showcase an ability to effectively communicate. Avoid rambling, vague or repetitive language and keep the tone positive and outcome-focused.

Double Check Schools’ Instructions

Read and re-read the school’s instructions for submitting a statement of purpose. Data science requires attention to detail. You don’t want to disqualify yourself by not following basic instructions. Make sure you meet all the stated requirements, and don’t make mistakes like exceeding word count or incorrectly formatting a document.

Proofread, Proofread and Proofread

Check your essay for any grammatical errors. While data scientists often deal with numbers more than writing, it’s still important to proofread because it will show the admissions committee you pay attention to details.

FAQs About Data Science Statements of Purpose

Before beginning your master’s in data science application, get answers to any final questions about statements of purpose. If you’re still unsure about the process, consider asking your admissions counselor.

Take the statement of purpose seriously. Often, it is the only part of your application where the admissions committee gets to hear directly from you. A well-crafted statement of purpose can help provide context around low test scores or grades as well as highlight how your experience has helped prepare you for the program.

Whether applying to a campus-based or  online master’s in data science , it’s better to start working on your statement of purpose earlier to ensure you have sufficient time to think and prepare. Since some master’s in data science programs may have rolling application and start dates, it’s best to double check admissions deadlines and make sure you have plenty of time to write and edit your statement of purpose.

Schools may have different requirements for statement of purpose submissions. Check directly with your school of interest. In general, keep statements of purpose concise—word counts may range from 250 to 1,000 words—and focused on academic and professional achievements that may help you succeed in a data science program.

Different schools have different word count requirements. Some schools will specify the length, but others do not. In general, a statement of purpose is between 300 and 500 words. Some schools allow up to 1,000 words. If word count isn’t explicitly stated, try to be concise. These are short essays. Writing a statement of purpose is one of the first steps toward studying and working in data science. If you want to better prepare for your application, it’s best to start searching for programs early to understand their requirements. Students can either look at  data science programs by state  or consider  data science scholarships available  for students.

Last updated: March 2022

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Sample Personal Statement Data Science

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Stanford Ph.D. Biomedical Data Science

My primary career objective is to bridge the distance between technical healthcare information within clinical information systems and the broader public’s understanding, using novel analytics methods as my tools. I fervently believe that developing user-centered design methods and computationally advancing health data delivery for patients and clinicians will allow for streamlined insights, greatly enhancing clinical decision-making, patient outcomes, and health equity.  Stanford Medicine’s Department of Biomedical Data Science (DBDS) has demonstrated its commitment to leveraging innovative data-centered techniques to advance the biomedical and healthcare domains. This renders DBDS the ideal setting for me to pursue an Academic Research MS in Biomedical Data Science. DBDS’s renowned faculty, emphasis on scientific communication, and comprehensive curriculum will equip me with the robust foundation required to revolutionize the dissemination of health data. Following this degree, I hope to pursue a PhD in Biomedical/Clinical Informatics, with the intention of entering industry to specialize in the design, development, and implementation of novel informatics tools to advance patient care. The pandemic revealed that scientific communication remains a significant barrier to healthcare equity. I recognize that prioritizing verbal and written communication alongside technical skills is critical to addressing this challenge. To build a strong qualitative and quantitative foundation, I chose Swarthmore College to pursue my undergraduate studies in Computer Science and Economics, with a minor in Biology. There, I developed a strong computational foundation, encompassing a deep comprehension of system operations, effective problem-solving, collaborative teamwork, and a self-starting mindset, enabling me to acquire the tools necessary to tackle complex problems. During my first two years at Swarthmore, I engaged in interdisciplinary projects promoting self-awareness, health, and well-being. These projects included using Python to employ six machine learning classifiers to predict personality types of social media users and developing a user interface with HTML, CSS, Python, JavaScript, SQL, and Flask for exploration of Swarthmore’s gym equipment and its uses. These projects sparked my interest in academic research and cultivated my inquisitive nature, inspiring me to seek a formal research mentorship for a project that closely aligns with my passion for biomedical data science and clinical informatics. Following my freshman year, I was awarded an NSF/DOD grant to conduct data analytics research at the University of Southern California Information Sciences Institute under Dr. John Heidemann. My primary task was to develop a public web application displaying shifts to COVID-19 Work- from-Home (https://covid.ant.isi.edu). To complete this project, I gained proficiency in five computer languages, including Python, JavaScript, HTML, CSS, and PHP, analyzed raw data in SQL from multiple databases to identify the optimal strategy for delivering information to users, and ascertained the relevant information to present. In particular, I chose to generate multi-tab pop- ups containing interactive line graphs for temporal changes and dynamic tables for Internet Service Provider information. I later extended and adapted my work for their ANT Outage World Map (https://outage.ant.isi.edu/). Equally as important, I gained firsthand experience operating within a research team, asking questions, incorporating feedback, and communicating progress on my project. Furthermore, I learned how to properly draft a publication as first author, undergo the review process, and present to and converse with professionals at the 2021 IEEE International Conference on Big Data (BigData). 1 To strengthen my ability to communicate our process to those beyond the field, I created and presented a poster at the University of Minnesota’s REU Poster Symposium. 2 These experiences were my first exposure to the complexities of effectively distilling complex information into easily understandable insights for those unfamiliar with the subject. In an effort to apply data analytics and advanced computational methods to the healthcare domain, I began working at Harvard Medical School’s Department of Biomedical Informatics under Dr. Nils Gehlenborg. I was selected to work on a research team committed to leveraging data science to generate detailed genomics visualizations to mitigate the challenges biomedical researchers face. Specifically, I applied an edge- bundling algorithm using TypeScript to the lab’s grammar- based genomics visualization toolkit known as Gosling (https://gosling.js.org). This edge-bundling algorithm reduced the visual clutter of the genomics visualizations, elucidating pertinent information to biomedical researchers and enabling the formation of hypotheses. To further refine my research skills and expand upon my knowledge of statistical methods, I am conducting bioinformatics research at Swarthmore with Dr. Rebecca Clements, applying computational methods in R to RNA sequencing data to investigate the immunological role of red blood cell progenitors during pregnancy. Additionally, I have remained involved in the research conducted by Heidemann’s lab due to my close affiliation with USC ISI. I was awarded an NSF grant to analyze statistical differences between two outage collection systems and draft a second publication as lead author. This paper is in its final stages of completion, and we intend to submit it to the appropriate conferences within the next three months. Witnessing the impact of simplifying complex health data greatly reinforced my determination to pursue a research-focused graduate degree. At DBDS, I look forward to engaging with an abundance of patient records as offered through the Stanford Hospital and Lucile Packard Children’s Hospital research clinical database. This access would enable my peers and I to analyze how they convey, synthesize, and integrate information from patients, providers, and researchers. My ability to bridge the gap between complex technical language, articulate writing, and effective verbal communication, coupled with a robust understanding of research methodology, has equipped me well for graduate-level academics and research. My ultimate goal is to increase health equity and elevate patient outcomes by improving the access to and comprehensibility of scientific information through novel computational methods. Stanford Medicine’s DBDS’s dedication to advancing biomedicine and healthcare through the representation and analysis of biomedical information makes it the optimal setting for completing an Academic Research MS in Biomedical Data Science.

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Writing a Business Analytics Masters Personal Statement

Table of Contents

For the most part, a business analytics masters personal statement serves as a self-description. Your educational background, career goals, plans, and accomplishments have shaped your professional path and are all essential to a personal statement.

Because it serves as the foundation upon which institutions pick or reject applicants, it is an essential component of the application package.

In this article, we’ll give examples and examine the elements that constitute a personal statement for Business Analytics.

What Is a Personal Statement for Business Analytics?

To apply for a job in business analytics, you’ll need to write a personal statement outlining your background, aspirations, and qualifications.

It is this statement that those in the admissions’ committee will read. It should cover your education, work history, passions, and aspirations.

The overall goal is to provide sufficient information to enable the admission officer to assess your fit into the business analytics program.

Points to Note When Writing a Personal Statement for a Masters in Analytics.

Accepting a Master’s in Business Analytics program can seem daunting. Here are a few points to note to help you write an effective personal statement:

• Mention internships, volunteer work, and other forms of community service are additional ways to show your interest in and dedication to the field.
• Be sure to highlight any relevant college courses you’ve taken, projects you’ve finished, accolades you’ve received, publications you’ve produced, or professional certifications you’ve earned.

Improve your chances by brushing up on the basics of analytics, such as;

• Conducting research into best practices
• Becoming acquainted with data models and applications,
• Building problem-solving abilities
• Mastering quantitative analysis tools.

Great Example of Business Analytics Masters Personal Statement

This personal statement is a fantastic INK example of the type of content you should include in your personal statement.

A Master’s program in Business Analytics offers a unique opportunity to master the art of data-driven decision-making. It also enables professionals to make better business decisions and excel in their chosen fields.

As an experienced professional, I am keenly aware of blending rigorous analytical techniques with strategic insight and intuition. Therefore, pursuing a Masters Program in Business Analytics is the ideal platform to refine my skill set and broaden my expertise.

The invaluable education and experiences gained will equip me with relevant theoretical knowledge and hands-on practicals to unlock new insights. Moreover, the ability to write clear and concise reports after analyzing complex data sets will be vital for communicating results and actionable insights succinctly.

I believe my interpersonal skills, including excellent communication abilities, strong problem-solving aptitude, and creative thinking capabilities, allude to success in this field.

Additionally, my knack for working effectively in teams promises to optimize any collaborative projects during the program.

With these assets under my belt, I intend to leverage the interdisciplinary approach presented by the Business Analytics Masters Program. I aim to succeed in a world increasingly driven by data-informed decisions.

A business analytics masters personal statement can provide a lot of insight into a candidate’s passion and potential value to the school . It should be focused on the candidate’s perspective, interests, and achievements.

Abir Ghenaiet

Abir is a data analyst and researcher. Among her interests are artificial intelligence, machine learning, and natural language processing. As a humanitarian and educator, she actively supports women in tech and promotes diversity.

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Msc data science personal statement example.

In the recent decade, the function of machine-generated intelligence in supplementing judgments has been more visible. It is reasonable to expect that in a few years, humans' role in decision-making processes will be limited to selecting the best possibilities from a collection of outputs supplied by computers. Machines are significantly more effective than human intelligence since the advent of Data Science. This is especially true when it comes to detecting trends, identifying patterns, and making predictions from large datasets. However, for such accomplishments, computers require the assistance of professional data scientists. I believe that pursuing the MS in Data Science from your respected university will enable me to pursue a rewarding career as a data scientist.

I graduated from the University of Ilorin's Department of Electrical and Electronics Engineering. The course provided me with a strong foundation in programming, web technologies, data structures, and DBM systems. Motivated by my desire to learn, I have attempted to dabble in a wide range of relevant topics that were not covered in the curriculum. The majority of these investigations were conducted via online courses from reputable colleges. Data Science, Machine Learning, and Blockchains are just a few of the topics I've mastered this way. Although such classes were limited to the fundamentals, the variety has assisted me in connecting the dots between diverse technologies.

My academic goals, on the other hand, have not prevented me from participating in a wide range of extracurricular activities. I was a member of the Phos Foundation where I was in charge of supporting in organizing charity programs and helping to solicit funds from notable people in the society. I watch movies a lot as it is one of my ways of relieving stress. My goal is to become a powerful data scientist and work as a researcher analyzing large data sets and creating models to further predict and explain their effects on the globe.

To get a comprehensive understanding of all the fields and divisions of technology that encompass data science, I have chosen to pursue a master's degree in data science. I'm confident that attending your university will provide me with the chance to pursue greatness and acquire the knowledge and skills necessary for a fruitful career in data science. As a result, I think learning more about data science will be useful because it is the future. With the information I will acquire from my master's degree, I hope to undertake insightful studies on huge data sets

My knowledge base has been widened by my prior education and work experience, which have given me a comprehensive understanding of the many fundamental fields that make up data science. Throughout my graduate and doctorate studies, I hope to delve further into this subject and uncover all of its possibilities. I had the good fortune to meet amazing individuals, build a solid network, and acquire some priceless analytics-related expertise during my education and professional career. I still have that childlike curiosity and want to advance, which for me would be to enrol in a Master's degree.

I think I still have a great deal to discover about this subject and a long way to go before I can accomplish my objectives. I am certain that the Data Science program at University of Sussex will help me increase my knowledge and hone my abilities so that I may fulfil my lifelong goal of becoming a powerful data scientist. The excellent academic staff and program at the university will give me exposure to and training in my area of interest, which will help me grow my career in the right direction. I thus ask for the chance to pursue a master's degree in the area of study of my choice since I would benefit from the university.

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Virtual Info Sessions

Interested in learning more about Binghamton University's Master of Science in Data Analytics program? Join us for a virtual info session!

You'll have the chance to get all of your questions answered, as we'll discuss eligibility, expectations, curriculum and the application process.

Register for an info session at this link.

Do I qualify for Binghamton University's MS in Data Analytics program?

• Applicants must have a bachelor's or graduate degree and a solid quantitative background.
• Students with degrees in mathematics, statistics or other applied sciences (business, economics, political science, engineering, etc.) are welcome to apply.
• Applicants are expected to have a GPA of 3.0 or above.
• Applicants with at least two years of work experience in a business or industrial setting are especially encouraged to apply.

More information about admissions requirements can be found here .

For students transferring in from another university, the Graduate School allows up to six credits to be transferred after a student has been admitted and has joined the program. The transfer of credits is subject to approval by the program director. Please reach out to [email protected]  for more information.

International students

We welcome international students to apply to the program.

International applicants must submit results from either TOEFL (minimum score of 80) or IELTS (minimum score 6.5)

International applicants should have a minimum of one year of work experience. Preference is given to applicants who have two or more years of work experience.

Find more information about additional required application materials for international students here .

Helpful links for international students:

• Office of International Students and Scholars Services (ISSS)
• New International Student Information
• Binghamton University Cultural Student Groups
• Binghamton University JFK-Binghamton Bus Service

The application

Requirements.

You can begin your application here . The application for fall 2023 will be available in early September.

Academic transcript(s), two letters of recommendation, a current resume and a personal statement (see below) are required along with the completed online application.

GRE or GMAT scores are accepted, but not required.

Personal Statement

The MS in Data Analytics admissions committee is looking for the following information in your personal statement:

• one to two pages
• two to three courses in your previous degree(s) that you liked and why
• details of any internship or work experience you have had in the past few years relevant to analytics
• any unusual features of your academic background, such as weak grades, and how you improved or prepared for graduate study
• career goals after completing the MS in Data Analytics degree

More information

More information about graduate study at Binghamton University can be found on The Graduate School website .

If you have any questions about the MS in Data Analytics program, contact:

Manoj Agarwal Program Director [email protected]  

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Last Updated: 8/27/24

Business Analytics Personal Statement Examples

Your business analytics personal statement (SOP) is a key component of your application to the Master of Business Analytics (MBA) program. Besides laying out your career goals, the SOP also should describe your skill set. If you have any weaknesses, discuss how you overcame them. In any case, your SOP should not exceed the word limit of the university. Be yourself, but don’t be too formal – your SOP should not be a resume.

Table of Contents

Writing a business analytics personal statement

The SOP should explain your motivation for pursuing a career in business analytics. In the first paragraph, you should briefly explain what prompted you to study this particular course. Your background, skills, and extracurricular activities should also be mentioned. In the third and fourth paragraphs, talk about your short and long-term career goals, and why you think these skills and interests are complementary. Be sure to keep your tone professional and positive throughout the entire essay.

When writing an SOP for Business Analytics, remember to think outside of the box and include relevant details about your background. Include your achievements in school and college. You can also include your professional history and highlight how your previous experiences helped you realize your interest in the Business world. You should also list down your programming skills and analytical skills. Make sure to mention your previous work experience if it relates to Business Analytics. Finally, remember to proofread your SOP before you send it off. Even a simple typo can make you appear unprofessional.

Structure of the SOP

The Structure of the SOP in business analytics personal statements should include a personal introduction that explains your traits, interests, and habits. It should also highlight your professional skills, including your work ethic, analytical skills, and willingness to work as part of a team. Lastly, it should describe the course you’re applying to, including which institutions you’ve applied to and why. In short, your SOP should show why you’re a good fit for the program.

The Structure of the SOP in business analytics personal statements should be interesting to read, and not too formal. Admission committees are looking for determinants of personality, so make your statement about yourself as real as possible. Ultimately, it will help the admissions committee understand who you are. Be yourself! Don’t over-emphasize your accomplishments and your experience. Make sure your statement is clear, concise, and well-written.

Be yourself in the SOP

While writing the Business Analytics personal statement, be yourself. You can begin by telling the reader why you want to study business analytics and then elaborate on your future goals. Don’t be too polished or overstate your achievements. Be real about your weaknesses and shortcomings, and emphasize how you overcame them. Avoid using overly formal language, especially when describing your past. The admissions committee wants to see the real you, so you should avoid sounding like an academic, but rather a business person.

In the Business Analytics personal statement, discuss your preferences for college and the courses you want to take. Include your interests, hobbies, and daily routine. Also, mention your skills and how you would work with a team. Make sure to talk about how you are willing to learn and work hard. If possible, mention your work experience. These experiences may prove to be helpful in your future career. The MBA program is competitive, so be honest about your experiences.

Check spelling and grammar

Before you start your statement, check your grammar and spelling for mistakes. Make sure to avoid using passive voice, cliches, and long sentences. Also, make sure to keep the tone professional. Avoid colloquialisms, hashtags, and casual language. This is your statement, and you want to convey your professionalism as best you can. Remember that your application is being read by prospective employers, so you’ll need to communicate clearly to them.

Business analytics personal statement

A statement of intention for USC business analytics is the fundamental document that is included in the business intelligence package. The structure of the document serves as an invitation for users to participate and submit their qualitative data to the analytics team. Data submitted are based on a variety of different factors, which range from overall business performance to specific customer attributes. Data obtained are used to form analytical reports which are then used to support strategic decisions.

• Several samples for this purpose have been created by a group of experts, who have worked together over many years to create the statement of intent for USC business analytics. The first data set for the statement of intention contained thousands of business and organizational attributes. This resulted in a massive quantity of qualitative data which was then processed into usable reports. More recent samples have focused on aspects such as diversity across cultures and skillsets. The breadth of the data and the quality of the analytical work done have both contributed to the recent success of the statement of intent.
• Another example of a statement of intent for USC business intelligence is the Usability Studies for US National Security which is an initiative developed by the Intelligence Studies Institute. The project was developed to support the National Data Entry Request for Data Management requirements and support the US Department of Defense and other national security agencies within their requirement process. The project involved the compilation of usability data for over one hundred thousand different users across all departments, all of which had different departments and different levels of involvement. Data for this project have been processed and submitted to the Intelligence Studies team for analysis.
• To support their business intelligence needs, some sample statements for the US National Security Agency (NSA) have been developed. The NSA is an extremely secretive and powerful national security agency. Its capabilities in foreign affairs and intelligence collection make it necessary that its human resources, analytic capability, and technical abilities are kept at the highest level of competence. A sample statement for the NSA might be “We develop and utilize analytical and research tools to maximize our collective understanding of foreign matters”.
• Business analytics personal statement examples may also look at a company’s IT function. These professionals are responsible for defending the information and systems of the company’s internal network. Some of the skills that might be required may be information security, computer networks, and data management. Companies that have a strong division of IT personnel may be more successful when recruiting the right person to serve as a business analyst. The statements from the Department of Defense and the Intelligence Studies teams at USC are a good starting point for selecting someone who will fit into the business intelligence role.

Some sample statements from business analysts can be considered the most common of these examples, although there are many others available as well. The US Department of Defense’s statement for its Human Resources Management team reads “The mission of the Human Resources Management element of the Department is to recruit, select, and promote individuals best suited to fill critical Human Resources positions in the Department and to train and retain the nation’s best Computer Systems Analysts.” The Intelligence Studies team at USC states “SCAs are experts in collecting and interpreting data using a wide range of techniques.” If you are writing a business case based on one of these examples, you should consult a computer science degree program or a graduate school before completing your write-up.

One Reply to “Business Analytics Personal Statement Examples”

I AM APPLYING TO STUDY BUSINESS ANALYTICS IN A UK UNIVERSITY AND I AM TRYING TO WRITE A PERSONAL STATEMENT FOR THE ADMISSION. I HAVE A BACGROUND IN BUSINESS INFORMATION SYSTEMS AND INTERNATIONAL BUSINESS PLEASE HOW CAN YOU HELP.

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PS - MSc International Business with Data Analytics

• Sample personal statement

05 August, 2022

Ps - msc international business with data analytics share.

• 12 May, 2013

The business environment is expanding, and globalisation is becoming the norm. Many companies are striving to keep up with these changes and they need graduates who can help them overcome these challenges. After much deliberation, I have decided to pursue MSc International Business with Data Analytics at University of Bedfordshire. The program provides its students with the knowledge and professional skills that go beyond the scope of standard management, and I believe that this program will give the premise to me to advance into a profession with extraordinary potential. In addition, this course also features different modules which will give me the opportunity to apply my theories and ideas in practice, and this will benefit me to enhance my skills and knowledge.

After completion of my Senior School Certificate, I have recently completed Bachelor of Science in Industrial Relations and Personal Management from Lagos State University, Lagos, Nigeria in April 2014. During my study, I was always involved in extracurricular activities and these activities have strengthened my abilities. In addition, I am a principled, dedicated youngster who is reliable and keen to learn new skills. I have been working as a Personal Executive for 5 years at Gems Communications Ltd. I gained valuable skills during my work period. Later, I have done a wide range of research on studying abroad. I believe studying abroad helps students to learn new languages, appreciate other cultures, overcome challenges of living in another country and gain a greater understanding of the world. In addition, these are the requirements that modern businesses look for when hiring, and such traits will only become more important in the future. Moreover, studying abroad also offers a unique opportunity to learn what we know but from a totally different perspective. These are the things which have motivated me to pursue this course at University of Bedfordshire. If I can successfully complete this course, it will create an opportunity to explore different career opportunities such as financial controller or manager, international economist, Business development manager, Policy advisor or analyst or Compliance officer at renowned companies in Nigeria such as Dangote Cement or Seplat Petroleum Development.

According to my research I have found that the MSc International Business with Data Analytics develops future leaders who can bring data skills and insight to their profession. I have read the modules, syllabus and learning outcomes of MSc International Business with Data Analytics which is intellectually stimulating and challenging. By studying this course, I will be able to gain the knowledge, understanding and skills relevant for pursuing a management career within a globally data driven environment. Moreover, it also improves independence, self-direction and self-development of participants for the benefit of the student, organisation and society. In addition, this course will provide an understanding of how these skills are applied at a more strategic level, transforming data into knowledge and insight that drives decisions. As I want to explore my career in business positions, this course will give an upper hand to understand any business contexts and situations. As of the moment, I am interested in learning all the related skills and knowledge from this course. For this reason, this course will be the right choice for my career plans and objectives. After completing this course, I want to come back to my country and establish my career in Managerial positions.

University of Bedfordshire offers units such as Accounting and Finance, Brand Communication and Reputation Management, Business Dissertation, Computer Networks and Security, Data Modelling, Management and Governance, Developing Independent Research, Intercultural Business Competencies, Performance Achievement Planning, Personal Professional Development and Strategic Management. All the modules are highly demanding and suitable to the today’s business world. For professionals, I believe that this course would be the right choice who are looking for a successful career in business sectors.

I am determined to study this course in the UK as the study environment in my country is quite different and we only have the opportunity to study with local students. Furthermore, due to periods of unexpected political unrest, students often struggle to finish their degrees on time. Conversely, the UK has a great multicultural and diversified student community which is an opportunity for me to learn with lot of students from different nationalities. UK education brand is highly respected by employers in our country as UK degree prepare graduates with academic competencies, developed personal and professional skills that are imperative for organizational success. The transferrable skills graduates carry forward from UK are pivotal for transforming organisational growth and gain competitive advantages. This is also a reason to study again in UK. In a recent Survey of International Graduate Outcomes 2019 by Universities UK International produced by iGraduate shows that 82% international graduates say that their UK degree are worth the financial investment and same percentage say they are satisfied or very satisfied with their careers. Nearly 83% feel that UK degree has helped them to get jobs. These aspects have driven my ambition to gain the degree from a UK institution. For this reason, I have decided to pursue this course in the UK.

The University of Bedfordshire is a modern, innovative university with a heritage of top- quality education. With over 22,000 students, we provide outstanding higher education to people from all backgrounds and from over 120 countries, with a significant proportion of mature students and a growing international postgraduate community. In addition, University of Bedfordshire has great industry links with more than 3,000 companies to provide a broad range of training and accredited professional courses for industry employers, including, BT, Sky, Boots, IBM, and the NHS, while the university educates professionals from 90% of FTSE 100 companies. University of Bedfordshire puts students on a fast track that is designed to get postgraduate degree into faster employment with excellent career opportunities. University of Bedfordshire’s modern Luton campus is located only 22 minutes from London with state-of-the-art facilities and innovative teaching methods supports the learning effectively. Moreover, University of Bedfordshire career support services help students build a successful career after graduation. This University brings workplace into classrooms so it will be beneficial for me to attain my personal career objectives by practicing in this type of learning environment. I will look no further if I get this chance to study this course at University of Bedfordshire. I sincerely believe that my talent will be put to optimal use, thereby helping me get closer to my career objectives and aspirations.

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BSc Economics, Finance and Data Science: writing a UCAS personal statement to impress

We are excited that you are considering applying for our new BSc Economics, Finance and Data Science course at Imperial College Business School. One of the things you will be wondering about is how to show your enthusiasm and suitability for the degree in your UCAS personal statement. In this blog, I will provide some pointers and, hopefully, reassurance.

The challenge

Let us start with the big challenge you face. You need to write one personal statement, when you are applying to up to five courses, potentially across five universities. We know that it is highly unlikely that all the options on your personal statement will be economics + finance + data science. We are not looking for students who specifically say they are only interested in studying a course with this combination of subjects, although an interest in this combination would be nice!

Hopefully, this will reassure those wondering how to write a statement that is relevant for multiple courses with different combinations of economics, finance, data science, philosophy, politics, business studies, geography, maths, computer science, and many other subjects. Of course, it is best not to signal that you are only interested in studying politics, philosophy and economics or pure maths or that you dream of studying at a particular institution or in a specific city.

We are looking for applicants who have a strong preference to study our degree, but we understand you may need to be nuanced in how you present your interest.

What we are looking for

We will be assessing your application (grade predictions; past grades; reference letter; and personal statement) in the round. There are six things that we are looking for from potential students . They are:

• Bright with strong academic achievements
• Excited by, and have strong potential for, analytical problem solving
• Curious to use economics and/or finance to explore evolving challenges in commercial, policy or third sector contexts
• Passionate to learn how to use data analysis and cutting-edge technique to examine economics and/or finance questions
• A motivated and engaged learner who works well independently and with others, with strong communication skills

Your job is to convince us that you have evidence that you meet these criteria. This is where you get to tell your story in a way that works for your application. 

How to tell your story

Try to go beyond your grades, show your curiosity and let us know what makes you stand out from an academic perspective.

There are a multitude of ways to evidence your curiosity about the different subjects in our degrees, including but not limited to:

• Subjects chosen at school
• Projects that you have worked on
• Talks that you have attended or listened to online
• Books you have read
• Ideas you have had about the relevance of these subjects to business and policy

Again, just to reassure, you can demonstrate your curiosity about all three areas, but convincing evidence of curiosity about just one of the areas or any combination of the three will also be well regarded.

It is also worth emphasising that we do not expect you to have studied the subjects before the course . Our requirement is that you come with strong mathematical skills which will put you in a strong position to learn economics, finance, and data science to a high level in the degree.

An effective way to show us you are suitable for the BSc Economics, Finance and Data Science is to hone in on the areas that are common across our course modules : strong quantitative skills and the ability to use those skills to analyse and solve problems.

Applicants who love to work on a new challenge or situation and who use quantitative techniques to find relevant solutions are what we are looking for. This can be demonstrated, for example, through your choice of academic subjects in school, participation in extra-curricular activities and competitions or a story that explains how you solved a new problem in your life. Evidence of you learning how to use technology to support your problem solving is also a nice touch!

You will have your own way of showing us that you are motivated, using examples of times when you were driven to succeed . Similarly, personal stories that show your ability to develop your learning skills (‘learn how to learn’), working independently and with others, will be important. This will help us see that you are likely to succeed in our course, given the need to take ownership of your learning, work independently and engage with group work during your three years.

Our final criterion is communication. How you write the statement will tell us a lot. You can also provide wider evidence of your skills in delivering presentations, writing diverse types of outputs, and listening to others.

Every applicant is unique, and we encourage you to show us what makes you a strong candidate in your personal statement . Of course, if you are invited to interview, we will want to explore your motivation to study the three subject areas together and will dig deeper into how you match what we are looking for.

I hope this helps you shape your statement and wish you well in preparing your application!

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Cassava, former execs ink SEC deal to resolve allegations around misleading Alzheimer's data drop

Cassava Sciences has  agreed to pay $40 million to resolve an investigation into claims it made misleading statements about phase 2b data on its Alzheimer’s disease drug candidate.

The U.S. Securities and Exchange Commission (SEC) set out the case against Cassava and two of the biotech’s former executives in a complaint  filed (PDF) Thursday. The case centers on the publication of data on PTI-125, also known as simufilam, in September 2020. Cassava reported improvements in cognition of up to 46% compared to placebo and went on to raise $260 million.

According to the SEC charges, the final results presented by Cassava were misleading in five ways. The charges include the accusation that Lindsay Burns, Ph.D., then a Cassava exec, now its co-defendant, removed 40% of the participants from an analysis of the episodic memory results.

The SEC said Burns, who was unblinded to the data, “removed the highest performing patients and lowest performing patients by baseline score cutoffs across all groups until the results appeared to show separation between the placebo group and the treatment arms.” The criteria for removing subjects was not predefined in the protocol.

At the time, Cassava said the effect sizes were calculated “after removing the most and least impaired subjects.” The biotech only admitted that the results excluded 40% of the patients in July 2024. 

The SEC also accused Cassava and Burns of failing to disclose that the candidate was no better than placebo on other measures of spatial working memory. 

On a cognition test, patients' average change in errors from baseline to Day 28 for the full episodic memory data was -3.4 points in the placebo group, compared to -2.8 points and -0.0 points, respectively, for the 50-mg and 100-mg simufilam groups, according to the SEC. Cassava’s presentation of the data  showed a -1.5 change on placebo and up to -5.7 on simufilam. Burns is paying $85,000 to settle her part of the case.

The SEC accusations poke holes in the case for simufilam that Cassava made for the drug when it shared the phase 2b data in 2020. However, Cassava CEO Rick Barry  said in a statement that the company is still hopeful that phase 3 trials “will be successful and that, after a rigorous FDA review, simufilam could become available to help those suffering from Alzheimer’s disease.”

Cassava, Burns and the third defendant, former CEO Remi Barbier, resolved the case without admitting or denying the allegations. Barbier agreed to pay $175,000 to resolve his part of the case, according to the SEC.

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FTC Staff Report Finds Large Social Media and Video Streaming Companies Have Engaged in Vast Surveillance of Users with Lax Privacy Controls and Inadequate Safeguards for Kids and Teens

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A new Federal Trade Commission staff report that examines the data collection and use practices of major social media and video streaming services shows they engaged in vast surveillance of consumers in order to monetize their personal information while failing to adequately protect users online, especially children and teens.

The staff report is based on responses to 6(b) orders issued in December 2020 to nine companies including some of the largest social media and video streaming services: Amazon.com, Inc., which owns the gaming platform Twitch; Facebook, Inc. (now Meta Platforms, Inc.); YouTube LLC; Twitter, Inc. (now X Corp.); Snap Inc.; ByteDance Ltd., which owns the video-sharing platform TikTok; Discord Inc.; Reddit, Inc.; and WhatsApp Inc.

The orders asked for information about how the companies collect, track and use personal and demographic information, how they determine which ads and other content are shown to consumers, whether and how they apply algorithms or data analytics to personal and demographic information, and how their practices impact children and teens.

“The report lays out how social media and video streaming companies harvest an enormous amount of Americans’ personal data and monetize it to the tune of billions of dollars a year,” said FTC Chair Lina M. Khan. “While lucrative for the companies, these surveillance practices can endanger people’s privacy, threaten their freedoms, and expose them to a host of harms, from identity theft to stalking. Several firms’ failure to adequately protect kids and teens online is especially troubling. The Report’s findings are timely, particularly as state and federal policymakers consider legislation to protect people from abusive data practices.”

The report found that the companies collected and could indefinitely retain troves of data, including information from data brokers, and about both users and non-users of their platforms. The staff report further highlights that many companies engaged in broad data sharing that raises serious concerns regarding the adequacy of the companies’ data handling controls and oversight. In particular, the staff report noted that the companies’ data collection, minimization and retention practices were “woefully inadequate.” In addition, the staff report found that some companies did not delete all user data in response to user deletion requests.

The staff report also found that the business models of many of the companies incentivized mass collection of user data to monetize, especially through targeted advertising, which accounts for most of their revenue. It further noted that those incentives were in tension with user privacy, and therefore posed risks to users’ privacy. Notably, the report found that some companies deployed privacy-invasive tracking technologies, such as pixels, to facilitate advertising to users based on preferences and interests.

Additionally, the staff report highlighted the many ways in which the companies fed users’ and non-users’ personal information into their automated systems, including for use by their algorithms, data analytics, and AI. The report found that users and non-users had little or no way to opt out of how their data was used by these automated systems, and that there were differing, inconsistent, and inadequate approaches to monitoring and testing the use of automated systems.

Furthermore, the staff report concluded that the social media and video streaming services didn’t adequately protect children and teens on their sites. The report cited research that found social media and digital technology contributed to negative mental health impacts on young users.

Based on the data collected, the staff report said many companies assert that there are no children on their platforms because their services were not directed to children or did not allow children to create accounts. The staff report noted that this was an apparent attempt to avoid liability under the Children’s Online Privacy Protection Act Rule . The staff report found that the social media and video streaming services often treated teens the same as adult users, with most companies allowing teens on their platforms with no account restrictions.

The report also noted some of the potential competition implications of the companies’ data practices. It noted that companies that amass significant amounts of user data may be in a position to achieve market dominance, which may lead to harmful practices with companies prioritizing acquiring data at the expense of user privacy. It noted that when there is limited competition among social media and video streaming services, consumers will have limited choices.

The staff report makes recommendations to policymakers and companies based on staff’s observations, findings, and analysis, including:

• Congress should pass comprehensive federal privacy legislation to limit surveillance, address baseline protections, and grant consumers data rights;
• Companies should limit data collection, implement concrete and enforceable data minimization and retention policies, limit data sharing with third parties and affiliates, delete consumer data when it is no longer needed, and adopt consumer-friendly privacy policies that are clear, simple, and easily understood;
• Companies should not collect sensitive information through privacy-invasive ad tracking technologies;
• Companies should carefully examine their policies and practices regarding ad targeting based on sensitive categories;
• Companies should address the lack of user control over how their data is used by systems as well as the lack of transparency regarding how such systems are used, and also should implement more stringent testing and monitoring standards for such systems;
• Companies should not ignore the reality that there are child users on their platforms and should treat COPPA as representing the minimum requirements and provide additional safety measures for children;
• The Companies should recognize teens are not adults and provide them greater privacy protections; and
• Congress should pass federal privacy legislation to fill the gap in privacy protections provided by COPPA for teens over the age of 13.

The Commission voted 5-0 to issue the staff report. Chair Khan , as well as Commissioners Alvaro Bedoya , Melissa Holyoak and Andrew N. Ferguson each released separate statements.

The lead attorneys on this matter are Jacqueline Ford, Ronnie Solomon and Ryan Mehm from the FTC’s Bureau of Consumer Protection.

The Federal Trade Commission works to promote competition and protect and educate consumers .  The FTC will never demand money, make threats, tell you to transfer money, or promise you a prize. Learn more about consumer topics at consumer.ftc.gov , or report fraud, scams, and bad business practices at  ReportFraud.ftc.gov . Follow the FTC on social media , read consumer alerts and the business blog , and sign up to get the latest FTC news and alerts .

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Statement from President Joe   Biden on the August PCE   Report

Today’s report shows inflation has come back down to 2.2%, similar to pre-pandemic levels, at a time when interest rates have fallen—lowering the cost of buying a home or car, or operating a small business. This follows yesterday’s news that on my watch the economy has grown more than 10% and incomes are up nearly $4,000, after accounting for inflation. The economy, incomes, savings, and consumer spending are all stronger than previously estimated.   We have more work to do to lower costs and create opportunities for Americans. The Vice President and I want to build millions of new homes, continue to lower the price of prescription drugs and health care, and cut taxes for families, small businesses, and industries of the future. Congressional Republicans would take the opposite approach—raising costs for middle-class families by nearly $4,000 per year while giving more tax cuts to the wealthy and big corporations. That’s not how you grow the economy, or the middle class.

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Sample Personal Statement Management and Analytics (LBS)

by Talha Omer, M.Eng., Cornell Grad

In personal statement samples by field.

Here is the personal statement of an applicant who got admitted to London Business Schools (LBS) Masters in Analytics and Management program . For personal statement, LBS poses several questions to applicants, which the admissions committee expects to be answered in an essay form. LBS provides these personal statement prompts to encourage students to self-reflect and then to share their insights with the program.

The following essays are an example of a compelling story and reflect the original voice and personality of the applicant. Get inspiration from them and try to incorporate their strengths into your own personal statement.

Related Personal Statements 1) Sample Personal Statement Business Analytics 2) Sample Personal Statement in Advanced Analytics (admitted to NCSU) 3) Sample Personal Statement in Analytics (admitted to Georgia Tech) 4) Sample Personal Statement in Data Science and Analytics (admitted to CMU and Vanderbilt)

In this Article

Personal Statement Prompt 1

Personal statement prompt 2, personal statement prompt 3, personal statement prompt 4.

Based on your current knowledge of the program, what do you think will be the key challenges for you during the Masters’s in Analytics and Management, both academically and personally? How do you intend to overcome these challenges?

I am genuinely excited by LBS’s plethora of academic and non-academic opportunities. I look forward to effectively utilizing the time to the best of my and my cohort’s advantage. However, academically and personally, such vast opportunities present challenges around prioritizing the most critical opportunities I need to be involved in since time constraints will limit the options I can take advantage of.

For this, I hope to be involved around the most focused personal and professional goals, which would be leveraging networking opportunities, active participation in Private Equity club events, volunteering in the Social Impact Club, and setting up a Boxing Club at LBS (to continue my extensive boxing routine). 

On an academic note, I believe that the MAM students will be exposed to complex data sets that require cleaning before further analysis or processing with machine learning. Since poor quality data correlates to lost revenue, effective data management practices are critical to obtaining optimal data analytics. While at Barclays Capital, I spent most of my time on data projects to clean the data. Before working at a hedge fund, I was an associate at PwC. I was responsible for creating the company’s first fully automated valuation process from first principles. It consisted of industry-specific valuation templates that would use analyst report data and an API through Barclay’s IQ to gather further information from the MD&A section to give a complete valuation. The challenge at PwC required analysts to spend considerable time on manual inputs. However, this solution saw significant savings for the firm and is used by PwC worldwide. Having spent time navigating the data management challenge, I look forward to applying the techniques learned and the practical exposure developed to take the LBS’ complex data deconstruction and analysis challenge. This will require learning new tools and methods, and I look forward to the opportunity. I also realize that teamwork is paramount for collective success in the modern world. Therefore, I look forward to sharing my expertise and learning from my peers in the process. This will amplify mutual gains manifold. 

Another major challenge at LBS will be to develop tangible solutions to real-world business problems. For this, initiatives such as the Global Immersion Field Trips and London LAB will offer the opportunity to challenge me both individually and as a team to evaluate real-life business problems. 

Since my goal is to enter hedge fund management, I need to upgrade my investment management analysis skills by learning advanced coding for efficient algorithm development. I would like to leverage my experience building a customized Algorithm at Barclays despite not knowing much about coding. I will try to challenge myself by actively taking courses and projects that provide the most opportunities to build this skill, and I will also learn from my more knowledgeable colleagues in the field in the process.

Lastly and most importantly, interacting with more than 11 nationalities with vastly diverse experiences in the class cohort will present challenges around understanding the vastly different cultural nuances, moving around language barriers, and understanding and appreciating their perspectives in the class and beyond. This will be vital for a transformational and well-rounded MAM experience. I intend to utilize my International experience of studying and working in Australia and Canada and my American perspective to make this transition smooth for me and my cohort.

To conclude, I believe every challenge is an opportunity for self-reflection and challenges one to grow out of comfort zone and succeed. Therefore, I eagerly await LBS’s challenges to convert them into life-changing learning opportunities. 

As an aspiring entrepreneur in investment and finance, the Masters in Analytics and Management program at LBS offers world-class learning opportunities to help me achieve my future career goals. Given my passion for financial analytics, I am enthusiastic about setting up a Quantitative Hedge Fund upon graduating from LBS. During my undergraduate, I co-founded a philanthropic Hedge Fund, The Australian Students Asset Management. The intervarsity fund aims to teach students the fundamentals of investing while donating the generated returns. In addition, I hope to expand on our current operations with a new “for-profit” fund focusing on statistical arbitrage trading strategies.

I have developed exposure to arbitrage trading strategies while working as an Analyst at Barclays Capital, a Global Hedge Fund. During my time with the fund, I learned basic programming like VBA and Python, which was critical in transforming my ideas into successful trading algorithms. With advanced, formal programming training, I can maximize the efficiency of these algorithms to decrease the time required to execute the programs and react to new market data sets effectively. With my ambitions lying in starting a quantitative hedge fund, the skills I learn in the MAM program will allow me to manipulate large data sets and automate trading decisions and executions. As such, the “machine learning” course is also fascinating for me as it will allow me to develop an understanding of deep learning and training neural networks to analyze a wide variety of data, including text, audio, and images. This will add new dimensions to my skill repertoire, currently limited to spreadsheet analysis. I am also eager to learn topics related to general dimension reduction techniques and Ensemble methods, as their use in forming accurate price derivatives would be invaluable.

Apart from building up my data analysis skills, I am eager to improve my management skills at LBS. My professional experience has helped me understand the importance of having a firm investment philosophy and vision to allocate capital efficiently, especially in times of poor performance and challenging external environments. I believe the program will equip me with the necessary tools and frameworks to create and communicate a similar sustainable management philosophy and develop a competitive advantage by tackling challenges from a strategic perspective. In addition, I aim to perfect the core problem-solving and decision-making skills that will provide me the confidence to operate a robust, successful global business model.

The MAM program will also allow me to interact with a diverse, talented, and global cohort of students along with the vast alumni base of LBS. During my time at LBS, I hope to build a solid and diverse network of current and future leaders in the Investment Management Industry to develop and appreciate multiple cultural and organizational perspectives. Ideally, I would love to bounce off entrepreneurial ideas with like-minded students and learn from mentors who have succeeded as entrepreneurs.

I also aspire to improve my interpersonal skills since it is as crucial as having technical skills like Data analysis for professional success.

Overall, the strength of the MAM program lies in its innovative programming and database curriculum coupled with extensive opportunities for developing strong interpersonal and management skills. As a MAM program graduate, I am confident that I will develop the proficiency to create a strong business impact in today’s complex and dynamic financial markets through active, well-rounded engagement inside and outside the classroom.

Describe a professional or academic data-driven project you have been involved with. What did you contribute to the project?

As an analyst at Barclays Capital, a leading quantitative hedge fund, I was assigned to independently create, develop and implement a systematic long/short pair trading strategy using every identifiable global oligopoly. The goal was to develop a scalable plan implemented across Australia and EMEA with a significantly high risk-adjusted return yield (>20%) by firm standards. 

The first task to develop the desired strategy was integrating and cross-valid multiple generals and industry-specific databases, including FactSet, Bloomberg, IBIS World, and Global Data. Working alongside my portfolio managers and senior analysts, I was responsible for thoroughly researching the accuracy and relevance of each database, which was then exhaustively reviewed and approved by the team.

Next, I had to measure firms’ market power in oligopolies to determine their industry influence. As only a few industries had directly available market share information, the task was immensely complex. I used the firm’s percentage of total industry revenue and production as the market power index, which required analyzing the financial data of every firm to determine its market share. I created an efficient VBA Excel Macro that collected data on over 540,000 firms to determine oligopolies for over 150 industry classifications.

Afterward, I evaluated the selected firms to determine possible long/short trading pairs within each industry. I identified firms with a consistent pricing relationship after analyzing historical data of 10 years to develop an algorithm that evaluated this big data set and determined pairs using mathematical principles around cointegration. I also developed a proprietary trading signal based on the probability of the mean reversion on pairs. Each pair had over 1,000 trades during the chosen time window and created problems in efficiency. I handled this challenge of analyzing over 400,000 trades by researching academic papers like ‘Risk and Return on Convertible Arbitrage’ by LBS researchers Naik and Fung and learning concepts like volatility trend analysis from my expert colleagues. 

The developed algorithm yields a highly desirable annualized return of 33%. Moreover, this project has allowed me to challenge myself by learning programming and VBA excel macro despite little experience. I also developed a deeper understanding of the mathematical principles involved in financial data science. Overall, it was a great learning experience, and I hope to build upon this experience during my time at LBS.  

How will you contribute to the School community during your time as a master’s in Analytics and Management student?

During my time at LBS, I will pursue my personal and professional passions such that I can uplift the overall MAM experience for the entire cohort. In addition, I will leverage the diversity of my experiences to contribute to a practical MAM experience for the school community. 

During my time at UNSW, I co-launched Australia’s first intervarsity long/short investment fund, Australian Students Asset Management (ASAM) which now includes a network of 40 mentors from reputable industry partners such as Goldman Sachs, Blackstone, and Point 72. I will utilize this entrepreneurial finance self-initiative experience and the skills learned to bring hands-on insights to class discussions to improve the learning experience for the entire class. This will be especially valuable for budding entrepreneurs fancying their chances in investment and entrepreneurial finance.

I am intrigued by the “beyond-classroom” opportunities at LBS. With societies like the Private Equity & Venture Capital Club and the Social Impact Hub, I aim to contribute outside the class to the school community. As a member of the Private Equity & Venture Capital club, I plan to participate in conferences like MultipleX, where I can learn from successful CEOs and company partners. In addition, I was a consultant at UNSW Social Impact Hub, where I led a group of 5 to access and structure a Social Impact Bond valued at $500,000, the largest of its kind in UNSW history. Leveraging this experience at LBS, I hope to also create a similar impact in this sphere. 

On a personal level, I want to bring my lifelong personal passion for boxing to LBS. Currently, LBS does not have a boxing society, and I would love to lead the opportunity of founding the “boxing society.” As an active member of the UNSW boxing society, I understand the nuances of running a sports society which will help smooth launching of the society at LBS. In addition, along with regular boxing events, I can lead the teaching of free self-defense classes to the LBS community, which is a critical skill in the modern day and age to ensure personal safety. 

In conclusion, I hope to make the best use of the opportunities at LBS to build a solid MAM experience for the entire community by bringing diverse perspectives to the table both inside and outside the classroom.

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Irish Data Protection Commission fines Meta Ireland €91 million

27th September 2024

The Data Protection Commission (DPC) has today announced its final decision following an inquiry into Meta Platforms Ireland Limited (MPIL). This inquiry was launched in April 2019, after MPIL notified the DPC that it had inadvertently stored certain passwords of social media users in ‘plaintext’ on its internal systems (i.e. without cryptographic protection or encryption).

The DPC submitted a draft decision to the other Concerned Supervisory Authorities across the EU/EEA in June 2024, as required under Article 60 of the GDPR. No objections to the draft decision were raised by the other authorities.

The decision, which was made by the Commissioners for Data Protection, Dr. Des Hogan and Dale Sunderland, and notified to MPIL yesterday September 26, includes a reprimand and a fine of €91million.

The DPC’s Decision records the following findings of infringement of the GDPR:

• Article 33(1) GDPR, as MPIL failed to notify the DPC of a personal data breach concerning storage of user passwords in plaintext;
• Article 33(5) GDPR, as MPIL failed to document personal data breaches concerning the storage of user passwords in plaintext;
• Article 5(1)(f) GDPR, as MPIL did not use appropriate technical or organisational measures to ensure appropriate security of users’ passwords against unauthorised processing; and
• Article 32(1) GDPR, because MPIL did not implement appropriate technical and organisational measures to ensure a level of security appropriate to the risk, including the ability to ensure the ongoing confidentiality of user passwords.

Deputy Commissioner at the DPC, Graham Doyle commented “ It is widely accepted that user passwords should not be stored in plaintext, considering the risks of abuse that arise from persons accessing such data. It must be borne in mind, that the passwords the subject of consideration in this case, are particularly sensitive, as they would enable access to users’ social media accounts. "

The DPC will publish the full Decision and further related information in due course.

In March 2019, MPIL notified the DPC that it had inadvertently stored certain passwords of social media users in ‘plaintext’ on its internal systems (i.e. without cryptographic protection or encryption). MPIL also published information regarding this incident in March 2019 [1] . These passwords were not made available to external parties.

The scope of the Inquiry, which commenced in April 2019, assessed MPIL’s compliance with the General Data Protection Regulation (GDPR), and in particular, whether MPIL implemented measures to ensure a level of security appropriate to the risks associated with the processing of passwords, and whether MPIL complied with its obligations to document, and notify the DPC of, personal data breaches.

This Decision of the DPC concerns the GDPR principles of integrity and confidentiality. The GDPR requires data controllers to implement appropriate security measures when processing personal data, taking into account factors such as the risks to service users and the nature of the data processing. In order to maintain security, data controllers should evaluate the risks inherent in the processing and implement measures to mitigate those risks. This decision emphasises the need to take such measures when storing user passwords.

The GDPR also requires data controllers to properly document personal data breaches, and to notify data protection authorities of breaches that occur. A personal data breach may, if not addressed in an appropriate and timely manner, result in damage such as loss of control over personal data. Therefore, when a controller becomes aware that a personal data breach has occurred, the controller should notify the supervisory authority without undue delay, in the manner prescribed by Article 33 GDPR.

The decision contains the following corrective powers:

• A reprimand pursuant to Article 58(2)(b) GDPR; and
• Administrative fines totalling €91 million pursuant to Articles 58(2)(i) and 83 GDPR.

Article 60 of the GDPR regulates the cooperation procedure between the Lead Supervisory Authority and the other Concerned Supervisory Authorities.

[1] Available at https://about.fb.com/news/2019/03/keeping-passwords-secure/

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• Volume 14, Issue 9
• Effect of volatile anaesthetic agents on intracranial pressure, cerebrovascular flow and autoregulation: a protocol for a systematic review and meta-analysis
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• http://orcid.org/0000-0003-3016-2230 Ben Taylor 1 , 2 , 3 , 4 ,
• Jack Ellis 4 ,
• Sam Ponty 2 ,
• Lewis Patrick 2 ,
• Timothy E Scott 1 , 3 , 4 ,
• http://orcid.org/0000-0002-7072-1271 Nachiappan Chockalingam 1
• 1 Staffordshire University Faculty of Health Sciences , Stoke-on-Trent , UK
• 2 Keele University Faculty of Medicine & Health Sciences , Keele , Staffordshire , UK
• 3 Academic Department of Military Anaesthesia and Critical Care , MOD , London , Greater London , UK
• 4 University Hospital of North Midlands , Stoke-on-Trent , UK
• Correspondence to Dr Ben Taylor; ben.taylor12{at}nhs.net

Introduction The use of volatile anaesthetic agents for the sedation of patients requiring critical care treatment offers several theoretical advantages over intravenous sedation, which may be of benefit in neurocritical care. However, there are concerns that they may increase intracranial pressure. The objective of this systematic review is to assess whether, and if so, to what extent volatile anaesthetic agents affect intracranial pressure, cerebral blood flow (CBF), cerebral oximetry and cerebrovascular autoregulation. If sufficient data exist, subgroup analyses will be conducted in traumatic brain injury and decompressive craniectomy patients.

Methods and analysis A database search of PubMed, Medline (including Medline plus), CINAHL (including CINAHL Plus), Embase databases and the Cochrane Central Controlled Trials Register without time limits will be conducted. The search results will be screened by title and abstract by two independent researchers on a rule-in basis against predetermined criteria—controlled studies in humans of contemporary fluorinated volatile anaesthetic agents against a control, which measures intracranial pressure, CBF, cerebral oximetry or cerebrovascular autoregulation. Articles responsive to screening will then be reviewed in full text by two independent researchers, requiring consensus or a tie-break by a third independent researcher. Reference lists and a non-generative AI tool will be examined for missed articles, with all identified articles being reviewed in full text by two independent researchers. The included articles will be assessed for risk of bias and will have data extracted by two independent researchers. If sufficient data exist, a meta-analysis will be performed; otherwise, a narrative description of outcomes will be performed.

Ethics and dissemination No ethics approval will be sought for this systematic review. This study has no explicit funding. The results of this study will be disseminated in a peer-reviewed journal, in a conference presentation and on PROSPERO.

Trial registration number PROSPERO number CRD42023474587

• adult anaesthesia
• systematic review
• anaesthesia in neurology
• intensive & critical care

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2024-086727

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STRENGTHS AND LIMITATIONS OF THIS STUDY

Expansive inclusion criteria will widely examine the extent of the literature on humans.

A predetermined, systematic, multi-stage review process will ensure the quality and accuracy of data.

Most studies are anticipated to be unblinded due to the nature of the interventions.

There is likely to be a substantial heterogeneity in study design and outcome measurement.

Many studies are likely to be small and low quality, which may limit the quality of the eventual outcomes.

Introduction

The volatile anaesthetic agents sevoflurane, isoflurane and desflurane are commonly used medicines in human anaesthesia. 1 Their use has expanded into critical care with the advent of reflector devices, which allow their administration with an intensive care ventilator, and they are helpful in some clinical settings with a need for further research into patient groups where they may benefit over intravenous sedation. 2 In principle, they have many features that potentially make them helpful in sedating patients following traumatic brain injury (TBI) 3 ―they are short-acting, allowing rapid neurological assessment. 4 In the general critical care population, their use may result in more ventilator-free days than propofol control. 5 They have anticonvulsant properties 6 7 and reduce cerebral metabolic rates in a dose-dependent fashion. 8 They may have neuroprotective effects. 9 Furthermore, they avoid known complications of the most commonly used alternative intravenous sedatives―propofol infusion syndrome 10 and prolonged sedation with an increased delirium risk with midazolam. 11

However, there are concerns about the risk of increased intracranial pressure (ICP) with volatile agents. 12 They are known to cause cerebral vasodilation, 13 and there are concerns, given the Monroe-Kellie doctrine, that this may increase intracranial pressure. 14 Although a survey of neurocritical care units in Germany demonstrated relatively widespread adoption of inhaled sedation in neurocritical care with few reported side effects, some respondents raised concerns and cited that they would consider TBI a contraindication. 15 Management of intracranial pressure is a core part of the neurocritical care management of patients with severe TBI. 16 17 A sustained rise in intracranial pressure is strongly associated with mortality and a worse outcome in TBI. 18

Volatile agents are increasingly used in neurocritical care. 15 In the absence of randomised controlled trial evidence comparing outcomes with volatile sedation against intravenous sedation, a review of the existing evidence base in humans is urgently required to address these concerns and identify gaps in the literature.

Some centres and clinicians consider the concern that volatile agents may elevate ICP as a relative contraindication to their use in this population. 15 However, the same survey demonstrates that other clinicians and centres use them in neurocritical care. It is currently unclear whether they affect ICP in this population and, if so, to what extent and if this would outweigh any potential benefits they may offer. There were similar concerns regarding ketamine, which was considered contraindicated where the ICP could be elevated until a similar review of the existing evidence base revealed that the strength of the recommendation was not justified. 19 20 Ketamine is now widely used as an emergency anaesthetic for patients with TBI. It is considered beneficial in maintaining favourable haemodynamics compared with other agents. 21

Aims and objectives

The overall aim of this systematic review is to evaluate the effect of volatile anaesthetic agents on intracranial pressure and the hypothesised mechanistic potential causes of ICP elevation with these agents.

The specific objectives are to answer the following research questions:

Do contemporary fluorinated volatile anaesthetic agents alter intracranial pressure in humans compared with alternative sedation or anaesthetic modalities?

Do contemporary fluorinated volatile anaesthetic agents alter cerebral blood flow (CBF), cerebral oxygen delivery or surrogate measures in humans compared with alternative sedation or anaesthetic modalities?

In humans, do contemporary fluorinated volatile anaesthetic agents impair cerebrovascular autoregulation compared with alternative sedation or anaesthetic modalities?

Is the effect of contemporary fluorinated volatile anaesthetic agents on intracranial pressure, CBF/oxygen delivery or cerebrovascular autoregulation different in humans with traumatic brain injuries compared with humans without traumatic brain injuries?

Is the effect of contemporary fluorinated volatile anaesthetic agents on intracranial pressure, CBF/oxygen delivery or cerebrovascular autoregulation different in humans with decompressive craniectomy compared with humans without decompressive craniectomy?

Does the effect of contemporary fluorinated volatile anaesthetic agents on intracranial pressure, CBF/oxygen delivery or cerebrovascular autoregulation modalities differ between agents and doses of each agent?

Methods and analysis

This protocol has been developed per the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). 22 This study has been prospectively registered with PROSPERO (CRD42023474587). Deviations from and any subsequent alterations to the protocol will be regularly updated on PROSPERO. The study will be started in June 2024 and is expected to last for approximately 6 months.

Study eligibility criteria

This systematic review will look at all published prospective human comparative studies that compare contemporary fluorinated volatile anaesthetic agents against any control and examine any reasonable index of CBF, surrogate measures, intracranial pressure or cerebrovascular autoregulation in any patient population. We will review all studies indexed in available medical databases.

Inclusion criteria

Controlled prospective trials of any methodology, including randomised controlled trials and crossover design trials.

Human participants in any clinical and resource settings, including healthy volunteers.

Participants have been administered any contemporary inhaled fluorinated volatile anaesthetic at any dose and duration.

A control or comparator is present in the study design.

The study measures CBF (including surrogate measures if described elsewhere in the literature), cerebrovascular autoregulation (using any described method for static or dynamic autoregulation), cerebral oximetry or intracranial pressure.

Exclusion criteria

Uncontrolled trials, including case series and case reports.

Review articles, opinions and editorials.

In vitro studies.

Animal studies.

Non-fluorinated anaesthetic agents (eg, chloroform, diethyl ether, trichloroethylene, nitrous oxide, xenon).

Fluorinated anaesthetic agents which are no longer commercially available (eg, enflurane).

Studies which cannot be translated reliably into English.

Papers where a full-text copy cannot be obtained.

Retracted papers.

Types of participants

The participants are any live humans enrolled in any comparative clinical trial where contemporary inhaled fluorinated volatile agents are administered as one of the arms of the trial.

Types of interventions

Patients to be included in this systematic review and meta-analysis will have received any contemporary fluorinated volatile anaesthetic by inhalation, at any concentration, and administered by any device including anaesthetic machines with vaporisers as would be typical in an operating theatre, draw-over anaesthetic apparatus, portable anaesthetic inhaler devices and disposable critical care anaesthetic vapour reflectors.

Studies may be included if their primary purpose was to examine the effect of different physiological conditions, such as different levels of arterial carbon dioxide.

As there is a reason to believe that each volatile anaesthetic has different properties, only agents currently in contemporary production for clinical use on a substantial scale globally will be included. The agents to be included are, therefore, as follows:

Sevoflurane

Methoxyflurane

Non-fluorinated inhaled anaesthetic agents belong to different pharmacological classes, differ substantially in chemical structure and physical properties and are less relevant to the background question of critical care sedation. Therefore, agents such as nitrous oxide, xenon, diethyl ether and chloroform will not be included as interventions. Intravenous sedative agents such as propofol will not be included as interventions.

Types of comparator

Only studies which compare the administration of contemporary volatile anaesthetics against a control will be included. Controls may be any of the following:

An intravenous sedative or anaesthetic agent.

Any other inhaled anaesthetic that may include non-contemporary or non-fluorinated agents.

Any suitable comparative trial design may include a randomised controlled trial with fixed allocation, an intention-to-treat basis or a crossover design.

Studies will not be included if the only control/comparator has no sedation or sedation with the same agent at a different dose. As only prospective studies will be included, case-control studies, case reports and case series will not be eligible for inclusion.

Studies will be eligible for inclusion if outcomes from any of the following groups are measured including in studies where these outcomes were secondary outcomes for that trial.

Intracranial Pressure

Direct measurements of intracranial pressure, including mean and maximum ICP

Time above an ICP threshold (22 or 25 mm Hg).

CBF measured directly by any validated method, including magnetic resonance imaging, radionuclide perfusion imaging and the Kety-Schmidt technique 23 .

Conventional indirect CBF measurements, including transcranial Doppler assessments of mean middle cerebral artery velocity.

Measures of cerebral vasodilatation, including digital subtraction angiography.

Cerebrovascular autoregulation

Any validated assessment of either static or dynamic cerebrovascular autoregulation.

Cerebral oximetry

Brain tissue oximetry and micro-dialysis.

Non-invasive infrared spectroscopy.

Jugular venous bulb saturations.

Database search

A systematic search of all relevant literature will be conducted using the following electronic databases:

Medline/Medline Plus

CINAHL/CINAHL Plus

Cochrane Central Controlled Trials Register

Given the long history of use and availability of agents that could be included in the review, no date limitation will be set aside from the search date. Figure 1 shows an example of the systematic search strategy to be used on Embase, and minor syntactical adjustments will be made as required depending on the syntax used for each database. The full search strings used for each database are available at Online Supplemental File 1 .

Supplemental material

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Embase search strategy. CBF, cerebral blood flow; CHS, coherent haemodynamics spectroscopy; ICP, increased intracranial pressure; MR, magnetic resonance; NIRS, non-invasive infrared spectroscopy; PET, positron emission tomography; SPECT, single photon emission computed tomography; Vmca, mean velocity of flow in the middle cerebral artery.

Other sources

The reference lists of included studies and any relevant excluded studies (eg, review articles, editorials and letters to the editor) will be screened for relevance to ensure that no studies are missed. Citation databases will be used to screen papers that cite included studies and relevant excluded articles, such as review articles.

Papers identified for inclusion will also be added to a non-generative AI tool (researchrabbit.ai) to further screen for potentially missed responsive articles.

Any studies identified through reference and citation trawls or using non-generative AI will be manually screened for suitability.

Data management

Studies identified from database queries will be uploaded to an online literature review tool (Rayyan.ai). Duplicate articles will be automatically and then manually removed. Data extraction of papers identified for inclusion will occur on Systematic Reviews Data Repository Plus ( https://srdrplus.ahrq.gov/ ), and extracted data will be processed using R V.4.3.2 with the ‘meta’ library installed.

Study selection

All papers identified through database searching will be screened in title and abstract form using Rayyan. Each paper will be examined by at least two authors working independently on a rule-in basis, and approval from any author will advance that paper to full-text review.

All papers approved by any author in that stage and any papers identified through reference, citation trawl or non-generative AI will be screened in full text by two authors working independently. Agreement between the screening authors will be required to advance the paper to inclusion and data extraction. The reasons for exclusion will be recorded. In the event of a disagreement, a third author who was not initially involved in advancing the study will mediate. Screening procedures will be presented using a PRISMA flow diagram.

Data extraction

Data will be extracted from all included studies by two reviewers working independently using a template in Systematic Review Data Repository Plus. If a disagreement on the extracted data cannot be resolved by discussion, a third reviewer will be asked to provide consensus. Data extraction will include the following information:

Study characteristics: title, first author, country, year of publication, study design, study size, resource setting

Clinical characteristics: age, gender, inhaled volatile anaesthetic(s) used, target concentration(s), control(s) used, target sedation depth in control. Identification of subgroups (TBI and decompressive craniectomy).

Intracranial pressure: any measure of intracranial pressure, the method used to measure ICP.

CBF: any measure of CBF, the method used to measure CBF.

Cerebrovascular autoregulation: any measure of static or dynamic cerebral autoregulation, the method used to assess autoregulation.

Cerebral oximetry: the method used, values.

Where data on inhaled volatile anaesthetic concentration is presented only as end-tidal gas concentration, this will be indexed to the minimum alveolar concentration for that agent in a 40-year-old using standard tables. 24–26

Assessment of risk of bias in included studies

The studies that are included will be scored for risk of bias at an individual study level using the Cochrane risk of bias tool (ROB-2). 27 The risk of bias will exclude no studies, as it is anticipated that allocation concealment will be difficult due to the nature and physical properties of the studied agents. However, the risk of bias will be used to illuminate the quality of the available evidence, and subgroup analyses may be performed in trials with a low risk of bias if sufficient evidence exists for any outcome. The risk of bias will be used to inform the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) of each outcome. Bias assessment will be reported using Funnel plots and Egger’s regression test. 28

Data synthesis and analysis

Data will be summarised by volatile agent and outcome where sufficient data allows comparison for that agent and outcome. A meta-analysis of these will be performed where there is sufficient continuous data from controlled trials for an agent against a single comparator. In this case, the heterogeneity of the available data will be evaluated using the I 2 and τ 2 statistics, and the standardised mean difference (95% CI) will be calculated for continuous outcomes and odds ratio (95% CI) for dichotomous outcomes. Meta-analysed data will be presented as a forest plot. A random effects model will be used unless there are a small number of studies (five or fewer) reporting for that endpoint, demonstrating high statistical and methodological homogeneity. 29

A narrative description will be performed where insufficient continuous or dichotomous data exist for a volatile agent and outcome.

The GRADE tool will be used for each outcome to communicate the strength of the body of evidence. 30

Missing data

Where a study would be eligible for inclusion but for missing outcome data, an attempt will be made to contact the corresponding author. Where data are only presented using a graphical form, an attempt will be made to contact the study’s authors. Where no response is heard, WebPlotDigitiser-4.6 (Ankit Rohatgi, Pacifica, CA, USA; https://automeris.io/WebPlotDigitizer ) will be used to estimate values.

Where sufficient continuous or dichotomous data exist to perform a meta-analysis, analysis of missing data due to publication bias will be assessed using a funnel plot and Eggers regression test. 28

Subgroup analysis

If sufficient responsive data exist, an a priori subgroup analysis will be conducted on the following:

Patients with TBI.

Patients with decompressive craniectomy.

Studies with a low risk of bias.

Sensitivity analysis

Where sufficient data exist to perform a meta-analysis, this will be reproduced following the removal of papers assessed to be at a high risk of bias or where the ‘metainf’ command within R indicates statistical indications of the excessive influence of a single paper.

Ethics statements

Patient consent for publication.

Not applicable.

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Contributors This work was proposed and initially drafted by BT who is the guarantor of this work under the supervision and with the advice of NC and TES. The protocol was developed through discussion and piloting by SP, LP and JE. This manuscript was initially drafted by BT. All other authors reviewed the draft manuscript, proofread it and were content with the article prior to submission.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, conducting, reporting or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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