Data Warehousing in the Age of Big Data

09/06/2013 · No Responses

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.
Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies
Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

Table of Contents
Part 1: Big Data
Chapter 1. Introduction to Big Data
Chapter 2. Complexity of Big Data
Chapter 3. Big Data Processing Architectures
Chapter 4. Big Data Technologies
Chapter 5. Big Data Business Value

Part 2: The Data Warehouse
Chapter 6. Data Warehouse
Chapter 7. Re-Engineering the Data Warehouse
Chapter 8 –Workload Management in the Data Warehouse
Chapter 9. New Technology Approaches

Part 3: Extending Big Data into the Data Warehouse
Chapter 10. Integration of Big Data and Data Warehouse
Chapter 11. Data Driven Architecture
Chapter 12. Information Management and Lifecycle
Chapter 13. Big Data Analytics, Visualization and Data Scientist
Chapter 14. Implementing The “Big Data” Data Warehouse

Appendix A. Customer Case Studies From Vendors
Appendix B. Building The HealthCare Information Factory