The state of the art and taxonomy of big data analytics: view from new big data framework

Big data has become a significant research area due to the birth of enormous data generated from various sources like social media, internet of things and multimedia applications. Big data has played critical role in many decision makings and forecasting domains such as recommendation systems, busin...

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Vydáno v:	The Artificial intelligence review Ročník 53; číslo 2; s. 989 - 1037
Hlavní autoři:	Mohamed, Azlinah, Najafabadi, Maryam Khanian, Wah, Yap Bee, Zaman, Ezzatul Akmal Kamaru, Maskat, Ruhaila
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Dordrecht Springer Netherlands 01.02.2020 Springer Springer Nature B.V
Témata:	Advertisements Advertising Analytics Application Artificial Intelligence Big Data Business Classification Computer Science Data analysis Data management Data processing Data systems Decision analysis Digital media Domains Economic sectors False advertising Forecasting Fraud Health care industry Health services Information systems Information technology Internet Internet of Things Interpersonal communication Literature reviews Marketing Mass media Mathematical analysis Multimedia Natural resource management Natural resources Networking Public sector Recommender systems Resource management Social media Social networks Social research Taxonomy Tourism Domain area Parallel and distributed computing Big data analytics techniques Big data tools
ISSN:	0269-2821, 1573-7462
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Abstract	Big data has become a significant research area due to the birth of enormous data generated from various sources like social media, internet of things and multimedia applications. Big data has played critical role in many decision makings and forecasting domains such as recommendation systems, business analysis, healthcare, web display advertising, clinicians, transportation, fraud detection and tourism marketing. The rapid development of various big data tools such as Hadoop, Storm, Spark, Flink, Kafka and Pig in research and industrial communities has allowed the huge number of data to be distributed, communicated and processed. Big data applications use big data analytics techniques to efficiently analyze large amounts of data. However, choosing the suitable big data tools based on batch and stream data processing and analytics techniques for development a big data system are difficult due to the challenges in processing and applying big data. Practitioners and researchers who are developing big data systems have inadequate information about the current technology and requirement concerning the big data platform. Hence, the strengths and weaknesses of big data technologies and effective solutions for Big Data challenges are needed to be discussed. Hence, due to that, this paper presents a review of the literature that analyzes the use of big data tools and big data analytics techniques in areas like health and medical care, social networking and internet, government and public sector, natural resource management, economic and business sector. The goals of this paper are to (1) understand the trend of big data-related research and current frames of big data technologies; (2) identify trends in the use or research of big data tools based on batch and stream processing and big data analytics techniques; (3) assist and provide new researchers and practitioners to place new research activity in this domain appropriately. The findings of this study will provide insights and knowledge on the existing big data platforms and their application domains, the advantages and disadvantages of big data tools, big data analytics techniques and their use, and new research opportunities in future development of big data systems.
AbstractList	Big data has become a significant research area due to the birth of enormous data generated from various sources like social media, internet of things and multimedia applications. Big data has played critical role in many decision makings and forecasting domains such as recommendation systems, business analysis, healthcare, web display advertising, clinicians, transportation, fraud detection and tourism marketing. The rapid development of various big data tools such as Hadoop, Storm, Spark, Flink, Kafka and Pig in research and industrial communities has allowed the huge number of data to be distributed, communicated and processed. Big data applications use big data analytics techniques to efficiently analyze large amounts of data. However, choosing the suitable big data tools based on batch and stream data processing and analytics techniques for development a big data system are difficult due to the challenges in processing and applying big data. Practitioners and researchers who are developing big data systems have inadequate information about the current technology and requirement concerning the big data platform. Hence, the strengths and weaknesses of big data technologies and effective solutions for Big Data challenges are needed to be discussed. Hence, due to that, this paper presents a review of the literature that analyzes the use of big data tools and big data analytics techniques in areas like health and medical care, social networking and internet, government and public sector, natural resource management, economic and business sector. The goals of this paper are to (1) understand the trend of big data-related research and current frames of big data technologies; (2) identify trends in the use or research of big data tools based on batch and stream processing and big data analytics techniques; (3) assist and provide new researchers and practitioners to place new research activity in this domain appropriately. The findings of this study will provide insights and knowledge on the existing big data platforms and their application domains, the advantages and disadvantages of big data tools, big data analytics techniques and their use, and new research opportunities in future development of big data systems.
Audience	Academic
Author	Wah, Yap Bee Mohamed, Azlinah Zaman, Ezzatul Akmal Kamaru Maskat, Ruhaila Najafabadi, Maryam Khanian
Author_xml	– sequence: 1 givenname: Azlinah surname: Mohamed fullname: Mohamed, Azlinah organization: Advanced Analytics Engineering Centre, Faculty Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) – sequence: 2 givenname: Maryam Khanian surname: Najafabadi fullname: Najafabadi, Maryam Khanian email: maryam.najafabadi@newinti.edu.my organization: Faculty of Information Technology, INTI International University & Colleges – sequence: 3 givenname: Yap Bee surname: Wah fullname: Wah, Yap Bee organization: Advanced Analytics Engineering Centre, Faculty Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) – sequence: 4 givenname: Ezzatul Akmal Kamaru surname: Zaman fullname: Zaman, Ezzatul Akmal Kamaru organization: Advanced Analytics Engineering Centre, Faculty Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) – sequence: 5 givenname: Ruhaila surname: Maskat fullname: Maskat, Ruhaila organization: Advanced Analytics Engineering Centre, Faculty Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM)
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ParticipantIDs	proquest_journals_3195886437 proquest_journals_2174596888 gale_infotracacademiconefile_A718215180 crossref_citationtrail_10_1007_s10462_019_09685_9 crossref_primary_10_1007_s10462_019_09685_9 springer_journals_10_1007_s10462_019_09685_9
PublicationCentury	2000
PublicationDate	2020-02-01
PublicationDateYYYYMMDD	2020-02-01
PublicationDate_xml	– month: 02 year: 2020 text: 2020-02-01 day: 01
PublicationDecade	2020
PublicationPlace	Dordrecht
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PublicationSubtitle	An International Science and Engineering Journal
PublicationTitle	The Artificial intelligence review
PublicationTitleAbbrev	Artif Intell Rev
PublicationYear	2020
Publisher	Springer Netherlands Springer Springer Nature B.V
Publisher_xml	– name: Springer Netherlands – name: Springer – name: Springer Nature B.V
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Title	The state of the art and taxonomy of big data analytics: view from new big data framework
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