eBook Data Warehousing in the Age of Big Data, 1st Edition

  • Published By:
  • ISBN-10: 0124059201
  • ISBN-13: 9780124059207
  • DDC: 005.745
  • Grade Level Range: College Freshman - College Senior
  • 370 Pages | eBook
  • Original Copyright 2013 | Published/Released June 2014
  • This publication's content originally published in print form: 2013
  • Price:  Sign in for price



Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn’t have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse.Learn how to leverage Big Data by effectively integrating it into your data warehouse.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Dedication Page.
About the Author.
1: Big Data.
2: Introduction to Big Data.
3: Working with Big Data.
4: Big Data Processing Architectures.
5: Introducing Big Data Technologies.
6: Big Data Driving Business Value.
7: The Data Warehousing.
8: Data Warehousing Revisited.
9: Reengineering the Data Warehouse.
10: Workload Management in the Data Warehouse.
11: New Technologies Applied to Data Warehousing.
12: Building the Big Data – Data Warehouse.
13: Integration of Big Data and Data Warehousing.
14: Data-Driven Architecture for Big Data.
15: Information Management and Life Cycle for Big Data.
16: Big Data Analytics, Visualization, and Data Scientists.
17: Implementing the Big Data – Data Warehouse – Real-Life Situations.
Appendix A: Customer Case Studies.
Appendix B: Building the Healthcare Information Factory.