Big-data

A Proposed Framework for Incorporating Big-data Technology in National Crisis Management Center, the Law and other Social Sciences

The chapter presents a framework for incorporating BDT in a traditional conceptual design of NCMC. The updated conceptual design is validated using the Analytical Hierarchy Process (AHP) and the Quality Function Deployment (QFD) technique. The results show that each requirement of national crisis is supported by a set of integrated modules of the conceptual design in a balanced way. The modules of the highest contribution in the design are the modules most related to BDT. The steps required for implementing the conceptual design are given.[1]

Adapting Big Data Ecosystem for Landscape of Real World Applications, the Law and other Social Sciences

Big data is revolutionizing world in the age of Internet. The wide variety of areas like online businesses, electronic health management, social networking, demographics, geographic information systems, online education etc. are gaining insight from big data principles. Big data is comprised of heterogeneous datasets which are too large to be handled by traditional relational database systems. An important reason for explosion of interest in big data is that it has become cheap to store volumes of data and there is a major rise in computation capacity. this subject aims at giving an overview of Big Data Ecosystem comprising various big data platforms useful in today’s competitive world.[1]

Big Data Time Series Stream Data Segmentation Methods, the Law and other Social Sciences

In this subject we introduce the Interval Sliding Window ISW and Interval Sliding Window and Bottom Up ISWAB algorithms, which are applicable to big data numerical time series data streams and uses as input the confidence level parameter rather than the maximum error threshold. The proposed algorithms has two advantages: first, it allows performance comparisons across different time series data streams without changing the algorithm settings, and second, it does not require preprocessing the original time series data stream in order to determine heuristically the reasonable error value. By our opinion these improvements are very efficient and important in context of big data tine series data streams processing. Finally, an empirical evaluation was performed on two types of time series data: stationary (normally distri[1]

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Notes and References

1. Dima Alberg, “Big Data Time Series Stream Data Segmentation Methods” (Encyclopedia of Information Science and Technology, 4th Edition, Information Resources Management Association, 2018)

Resources

Notes and References

1. Jyotsna Wassan, “Adapting Big Data Ecosystem for landscape of Real World Applications” (Encyclopedia of Information Science and Technology, 4th Edition, Information Resources Management Association, 2018)

Resources

Notes and References

1. Magdy Kabeil, Ahmad Kabil, “A Proposed Framework for Incorporating Big-Data Technology in National Crisis Management Center” (Encyclopedia of Information Science and Technology, 4th Edition, Information Resources Management Association, 2018)

Hierarchical Display of Big data

Education And Communications > Information and information processing > Information policy

Big data

Concept of Big data

See the dictionary definition of Big data.

Characteristics of Big data

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Resources

Translation of Big data

• Spanish: Macrodatos
• French: Mégadonnées
• German: Big Data
• Italian: Big data
• Portuguese: Megadados
• Polish: Duże zbiory danych

Thesaurus of Big data

Education And Communications > Information and information processing > Information policy > Big data

See also

• Data processing
• Personal data
• Data collection
• Data recording
• Database
• Information storage
• Coding
• Decision-making
• Digital single market

• Big data technology
• Big data analytics
• Mass data
• Large data set