Software architectures for big data: a systematic literature review
Big Data systems are often composed of information extraction, preprocessing, processing, ingestion and integration, data analysis, interface and visualization components. Different big data systems will have different requirements and as such apply different architecture design configurations. Hence a proper architecture for the big data system is important to achieve the provided ...
(PDF) Big data architecture evolution
University of North Dakota, USA. 3950 Campus Road, Stop 9015. Grand Forks, ND 58202-9015. +701.777.4133. [email protected]. ABSTRACT. This paper aims at developing th e Big Data Architecture, and ...
Big Data: Definition, Architecture & Applications
Big data system design can be costly due to infrastructure costs, steep learning curves for frameworks, and complexities in architectures [4]. While many common design elements exist such as the ...
PDF Software architectures for big data: a systematic literature review
Study 40: A novel architecture of big data for assessing the city traffic state is proposed in this paper. A real time, highly scalable system is among the architectural goals. The implementation is based on Hadoop and Spark. Various clustering methodologies like DBSCAN, K-Means, and Fuzzy C-Means are implemented.
Big Data Software Architectures: An Updated Review
This paper reports the main results of the performed systematic mapping with architecture-related requirements and modules relevant to software architectures for these systems and whether existing proposals of reference architectures to BDS encompass these elements. ... Xiaofeng, L., Jing, L.: Research on Big Data reference architecture model ...
Big Data Architectures : A detailed and application oriented review
oriented review. Abstract — Big Data refers to huge amounts of. heterogeneous data from both traditional and new sources, growing at a higher rate than ever. Due to their high. heterogeneity, it ...
Integrating Data Quality in Industrial Big Data Architectures: An
In this study, we aim to formulate design principles to support systematically incorporating data quality testing into big data architectures. For this purpose, we performed an action design research study at a large organization in the Netherlands.
Big Data Architecture and Reference Models
A reference architecture for big data interoperability is proposed in the document [3]. This model divides a big data system into system coordinator, data provider, data application provider, data framework provider, and data consumer from the perspective of system role division. Security, privacy and management run through the five components.
Building a Big Data Architecture
A big data architecture consists of the components, processes, and technology needed to extract, store, and process large volumes of data. As shown in Figure 3-1, the four core components of big data architecture are data ingestion and processing, data analysis, data visualization, and data governance. Figure 3-1.
15 years of Big Data: a systematic literature review
Big Data is still gaining attention as a fundamental building block of the Artificial Intelligence and Machine Learning world. Therefore, a lot of effort has been pushed into Big Data research in the last 15 years. The objective of this Systematic Literature Review is to summarize the current state of the art of the previous 15 years of research about Big Data by providing answers to a set of ...
The State of Big Data Reference Architectures: A ...
Big Data (BD) is a nascent term emerged to describe large amount of data that comes in different forms from various channels. In modern world, users are the ceaseless generators of structured, semi-structured, and unstructured data that if gleaned and crunched precisely, will reveal game-changing patterns. While the opportunities exist with BD, the unprecedented amount of data has brought ...
Big Data and cloud computing: innovation opportunities and challenges
3.8. Data architecture. Big Data is gradually transforming the way scientific research is conducted as evidenced by the increasingly data-driven and the open science approach (Jagadish et al. Citation 2014). Such transformations pose challenges to system architecture.
Reference Architecture and Classification of Technologies, Products and
The contribution of this paper is reference architecture for big data systems, and classification of related technologies and products/services. First, big data research, reference architectures, and use cases are surveyed from literature. ... Research on big data reference architectures is presented in Section 3.2. The latest reports of big ...
A reference architecture for big data systems
Over dozens of years, applying new IT technologies into organizations has always been a big concern for business. Big data certainly is a new concept exciting business. To be able to access more data and empower to analysis big data requires new big data platforms. However, there still remains limited reference architecture for big data systems. In this paper, based on existing reference ...
Big Data Management for Healthcare Systems: Architecture, Requirements
The contribution of this research paper is to propose an extensible big data architecture for healthcare applications formed by several components capable of storing, processing, and analyzing the high amount of data in real time and batch modes. This paper demonstrates the potential of using big data analytics in the healthcare domain to find ...
Software architectures for big data: a systematic literature review
The study aims to investigate the big dat a software architectures based on appli-. cation domains assessing the evidence cons idering the interrelation among the data. extraction area and the ...
Roles and Capabilities of Enterprise Architecture in Big Data Analytics
Organizations are attempting to harness the power of big data analytics. Enterprise architecture can be used as an instrument to integrate big data analytics into the existing IT landscape and enabling the development of capabilities to create value from these technologies. Yet, there is limited research about the role of enterprise architecture in adopting big data analytics. This paper ...
A comprehensive and systematic literature review on the big data
The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for ...
Big IoT Data Analytics: Architecture, Opportunities, and Open Research
This paper investigates the state-of-the-art research efforts directed toward big IoT data analytics. The relationship between big data analytics and IoT is explained. Moreover, this paper adds value by proposing a new architecture for big IoT data analytics. Furthermore, big IoT data analytic types, methods, and technologies for big data ...
When we talk about Big Data, What do we really mean? Toward a more
The absence of data-intensive subjects in our review suggests that some disciplines may be utilizing Big Data technologies without explicitly using the term "Big Data" in their research papers. One hypothesis is that computer science and related fields may consider the scale of data used as the norm, hence not explicitly mentioning "Big ...
Secure big data ecosystem architecture: challenges and solutions
Big data ecosystems are complex data-intensive, digital-physical systems. Data-intensive ecosystems offer a number of benefits; however, they present challenges as well. One major challenge is related to the privacy and security. A number of privacy and security models, techniques and algorithms have been proposed over a period of time. The limitation is that these solutions are primarily ...
Big Data Reference Architectures, a systematic literature review
an architecture that supports the orchestration of Big Data systems; an image of the system providing. with clear understanding of different elements and th eir interdependencies. Reference ...
The Use and Usefulness of Big Data in Finance: Evidence ...
Alternative data have become a new source of information for investors. This paper examines how this development is reshaping the role of sell-side analysts. Employing textual analysis of analysts' written reports, we show that analysts themselves have begun to adopt alternative data in their analyses.
Big data applications: overview, challenges and future
The big data market is expected to have remarkable growth globally, with revenue projections ranging to USD 473.6 Billion by 2030, reflecting a growth rate of 12.7% from 2022 to 2030 (Research and Consulting 2023).This substantial growth underscores the increasing recognition of big data's critical role across industries and sectors.
Big Data Architectures for Vehicle Data Analysis
In this paper, we consider Big Data applications for connected vehicles, where vehicle data is sent several times per second, permitting fine-grained and near real-time analysis of vehicle status and operating behavior. We focus on typical streaming applications and present implementations in Apache Spark and Apache Flink in different architectures and analyze several aspects of Big Data ...
PDF Data collection architecture for Big Data
This paper introduces two components in a data sharing architecture for big data. It presents the state of the art as basis for a research agenda. Aspects like ransport, storage, and processing are important for big data, but not addressed by this paper. 1.
From document-centric to data-centric public service provision
In this section, we evaluate the feasibility of the proposed data-driven architecture using as test bed the information provided by the Greek governmental entity MITOS (National Registry of Administrative Public Services) [MITOS 2023]. MITOS is the official registry of Greek public service documentation and descriptions.
Scalable Implementation of Random Forests for Big Data Classification
In the present times of big data, it is very crucial than before to utilize Random Forests for big-scale sorting jobs in the cloud. ... This research is a big stride toward solving the issues that are associated with classifying big data by generating a strong, adaptable, ... Cite this paper. Raparthi, M., Soni, M., Tiwari, V., Dhumane, A ...
COMMENTS
Big Data systems are often composed of information extraction, preprocessing, processing, ingestion and integration, data analysis, interface and visualization components. Different big data systems will have different requirements and as such apply different architecture design configurations. Hence a proper architecture for the big data system is important to achieve the provided ...
University of North Dakota, USA. 3950 Campus Road, Stop 9015. Grand Forks, ND 58202-9015. +701.777.4133. [email protected]. ABSTRACT. This paper aims at developing th e Big Data Architecture, and ...
Big data system design can be costly due to infrastructure costs, steep learning curves for frameworks, and complexities in architectures [4]. While many common design elements exist such as the ...
Study 40: A novel architecture of big data for assessing the city traffic state is proposed in this paper. A real time, highly scalable system is among the architectural goals. The implementation is based on Hadoop and Spark. Various clustering methodologies like DBSCAN, K-Means, and Fuzzy C-Means are implemented.
This paper reports the main results of the performed systematic mapping with architecture-related requirements and modules relevant to software architectures for these systems and whether existing proposals of reference architectures to BDS encompass these elements. ... Xiaofeng, L., Jing, L.: Research on Big Data reference architecture model ...
oriented review. Abstract — Big Data refers to huge amounts of. heterogeneous data from both traditional and new sources, growing at a higher rate than ever. Due to their high. heterogeneity, it ...
In this study, we aim to formulate design principles to support systematically incorporating data quality testing into big data architectures. For this purpose, we performed an action design research study at a large organization in the Netherlands.
A reference architecture for big data interoperability is proposed in the document [3]. This model divides a big data system into system coordinator, data provider, data application provider, data framework provider, and data consumer from the perspective of system role division. Security, privacy and management run through the five components.
A big data architecture consists of the components, processes, and technology needed to extract, store, and process large volumes of data. As shown in Figure 3-1, the four core components of big data architecture are data ingestion and processing, data analysis, data visualization, and data governance. Figure 3-1.
Big Data is still gaining attention as a fundamental building block of the Artificial Intelligence and Machine Learning world. Therefore, a lot of effort has been pushed into Big Data research in the last 15 years. The objective of this Systematic Literature Review is to summarize the current state of the art of the previous 15 years of research about Big Data by providing answers to a set of ...
Big Data (BD) is a nascent term emerged to describe large amount of data that comes in different forms from various channels. In modern world, users are the ceaseless generators of structured, semi-structured, and unstructured data that if gleaned and crunched precisely, will reveal game-changing patterns. While the opportunities exist with BD, the unprecedented amount of data has brought ...
3.8. Data architecture. Big Data is gradually transforming the way scientific research is conducted as evidenced by the increasingly data-driven and the open science approach (Jagadish et al. Citation 2014). Such transformations pose challenges to system architecture.
The contribution of this paper is reference architecture for big data systems, and classification of related technologies and products/services. First, big data research, reference architectures, and use cases are surveyed from literature. ... Research on big data reference architectures is presented in Section 3.2. The latest reports of big ...
Over dozens of years, applying new IT technologies into organizations has always been a big concern for business. Big data certainly is a new concept exciting business. To be able to access more data and empower to analysis big data requires new big data platforms. However, there still remains limited reference architecture for big data systems. In this paper, based on existing reference ...
The contribution of this research paper is to propose an extensible big data architecture for healthcare applications formed by several components capable of storing, processing, and analyzing the high amount of data in real time and batch modes. This paper demonstrates the potential of using big data analytics in the healthcare domain to find ...
The study aims to investigate the big dat a software architectures based on appli-. cation domains assessing the evidence cons idering the interrelation among the data. extraction area and the ...
Organizations are attempting to harness the power of big data analytics. Enterprise architecture can be used as an instrument to integrate big data analytics into the existing IT landscape and enabling the development of capabilities to create value from these technologies. Yet, there is limited research about the role of enterprise architecture in adopting big data analytics. This paper ...
The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for ...
This paper investigates the state-of-the-art research efforts directed toward big IoT data analytics. The relationship between big data analytics and IoT is explained. Moreover, this paper adds value by proposing a new architecture for big IoT data analytics. Furthermore, big IoT data analytic types, methods, and technologies for big data ...
The absence of data-intensive subjects in our review suggests that some disciplines may be utilizing Big Data technologies without explicitly using the term "Big Data" in their research papers. One hypothesis is that computer science and related fields may consider the scale of data used as the norm, hence not explicitly mentioning "Big ...
Big data ecosystems are complex data-intensive, digital-physical systems. Data-intensive ecosystems offer a number of benefits; however, they present challenges as well. One major challenge is related to the privacy and security. A number of privacy and security models, techniques and algorithms have been proposed over a period of time. The limitation is that these solutions are primarily ...
an architecture that supports the orchestration of Big Data systems; an image of the system providing. with clear understanding of different elements and th eir interdependencies. Reference ...
Alternative data have become a new source of information for investors. This paper examines how this development is reshaping the role of sell-side analysts. Employing textual analysis of analysts' written reports, we show that analysts themselves have begun to adopt alternative data in their analyses.
The big data market is expected to have remarkable growth globally, with revenue projections ranging to USD 473.6 Billion by 2030, reflecting a growth rate of 12.7% from 2022 to 2030 (Research and Consulting 2023).This substantial growth underscores the increasing recognition of big data's critical role across industries and sectors.
In this paper, we consider Big Data applications for connected vehicles, where vehicle data is sent several times per second, permitting fine-grained and near real-time analysis of vehicle status and operating behavior. We focus on typical streaming applications and present implementations in Apache Spark and Apache Flink in different architectures and analyze several aspects of Big Data ...
This paper introduces two components in a data sharing architecture for big data. It presents the state of the art as basis for a research agenda. Aspects like ransport, storage, and processing are important for big data, but not addressed by this paper. 1.
In this section, we evaluate the feasibility of the proposed data-driven architecture using as test bed the information provided by the Greek governmental entity MITOS (National Registry of Administrative Public Services) [MITOS 2023]. MITOS is the official registry of Greek public service documentation and descriptions.
In the present times of big data, it is very crucial than before to utilize Random Forests for big-scale sorting jobs in the cloud. ... This research is a big stride toward solving the issues that are associated with classifying big data by generating a strong, adaptable, ... Cite this paper. Raparthi, M., Soni, M., Tiwari, V., Dhumane, A ...