Description

Book Synopsis

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques. Data analytics are becoming an essential component for every organization and technologies such as health care, financial trading, Internet of Things, Smart Cities or Cyber Physical Systems. However, these diverse application domains give rise to new research challenges. In this context, the book provides a broad picture on the concepts, techniques, applications, and open research directions in this area. In addition, it serves as a single source of reference for acquiring the knowledge on emerging Big Data Analytics technologies.



Table of Contents

Part 1: Introduction to Data Analytics. 1. Techniques. 2. Classification. 3. Clustering. 4. Anomaly Detection. 5. Pattern Mining. Part 2: Tools for Data Analytics. 6. R. Hadoop. 7. Spark. 8. Rapid Miner. Part 3: Applications. 9. Health Care. 10. Internet of Things. 11. Cyber Security. Part 4: Futuristic Applications and Challenges.

Data Analytics

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A Paperback by Mohiuddin Ahmed, Al-Sakib Khan Pathan

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    View other formats and editions of Data Analytics by Mohiuddin Ahmed

    Publisher: Taylor & Francis Ltd
    Publication Date: 6/30/2020 12:00:00 AM
    ISBN13: 9780367570989, 978-0367570989
    ISBN10: 036757098X

    Description

    Book Synopsis

    Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques. Data analytics are becoming an essential component for every organization and technologies such as health care, financial trading, Internet of Things, Smart Cities or Cyber Physical Systems. However, these diverse application domains give rise to new research challenges. In this context, the book provides a broad picture on the concepts, techniques, applications, and open research directions in this area. In addition, it serves as a single source of reference for acquiring the knowledge on emerging Big Data Analytics technologies.



    Table of Contents

    Part 1: Introduction to Data Analytics. 1. Techniques. 2. Classification. 3. Clustering. 4. Anomaly Detection. 5. Pattern Mining. Part 2: Tools for Data Analytics. 6. R. Hadoop. 7. Spark. 8. Rapid Miner. Part 3: Applications. 9. Health Care. 10. Internet of Things. 11. Cyber Security. Part 4: Futuristic Applications and Challenges.

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