Modernize Data Warehousing with Hadoop, Data Virtualization, and In-Memory Techniques
TDWI Speaker: Philip Russom, TDWI Research Director
Date: Thursday, July 24, 2014
Time: 9:00 a.m. PT, 12:00 p.m. ET
Webinar Abstract
A growing number of user organizations are under pressure to capture and manage big data, as well as get business value from big data by analyzing it. To achieve these goals, many organizations are extending and revamping their data warehouse (DW) environments. According to TDWI surveys, the new technologies being adopted most by users who are modernizing their DWs include:
- Hadoop
- Data virtualization
- In-memory techniques
These are experiencing rapid user adoption, because they provide unprecedented levels of scale, flexibility, and speed.
This TDWI Webinar presents the business and technology reasons each of these has achieved new importance in recent years. The Webinar also shows how all three can be applied together in new data warehouse architectures and analytic applications.
You will learn:
- Business and technology reasons for embracing big data, advanced analytics, Hadoop, virtualization, and various in-memory technologies
- New types of analytics that depend on big data, virtualization, and in-memory processing
- How Hadoop (and big data, in general), virtualization, and in-memory processing are influencing data warehouse architectures and best practices in analytics
- How and why Hadoop, virtualization, and in-memory come together in a “perfect storm” with certain applications in data warehousing and analytics
Philip Russom, Ph.D.