Big Data
eBook - ePub

Big Data

Concepts, Warehousing, and Analytics

  1. 314 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Big Data

Concepts, Warehousing, and Analytics

About this book

Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved decision-making processes.

The concept of a Big Data Warehouse (BDW) is emerging as either an augmentation or a replacement of the traditional Data Warehouse (DW), a concept that has a long history as one of the most valuable enterprise data assets. Nevertheless, research in Big Data Warehousing is still in its infancy, lacking an integrated and validated approach for designing and implementing both the logical layer (data models, data flows, and interoperability between components) and the physical layer (technological infrastructure) of these complex systems.

This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.

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Yes, you can access Big Data by Maribel Yasmina Santos,Carlos Costa in PDF and/or ePUB format, as well as other popular books in Medicine & Energy. We have over one million books available in our catalogue for you to explore.

Information

Year
2022
Print ISBN
9788770221849
eBook ISBN
9781000797190
Edition
1
Subtopic
Energy

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication
  7. Table of Contents
  8. List of Figures
  9. List of Tables
  10. The Authors
  11. Acknowledgments
  12. Foreword
  13. Notation
  14. 1. Introduction
  15. 2. Big Data Concepts, Techniques, and Technologies
  16. 3. OLTP-oriented Databases for Big Data Environments
  17. 4. OLAP-oriented Databases for Big Data Environments
  18. 5. Design and Implementation of Big Data Warehouses
  19. 6. Big Data Warehouses Modeling: From Theory to Practice
  20. 7. Fueling Analytical Objects in Big Data Warehouses
  21. 8. Evaluating the Performance of Big Data Warehouses
  22. 9. Big Data Warehousing in Smart Cities
  23. 10. Conclusion
  24. References
  25. Index