Extreme Data Warehousing Webinar

Topic: Power Briefing: Extreme Data Warehousing for Massive Scale Analytics, Straight Talk From The Experts
Hosted By: Jim Kobielus, Sr. Analyst, Forrester Research
with Pat Richards, VP of Technical Operations, Fox Interactive Media
Duration: 50 Minutes
Format: 20 minutes – analyst gives presentation on need for companies to build long-term data warehousing strategy, offers tips on how to begin their search for the right solution and the capabilities they will need.
15 minutes – Analyst speaks with customer about how they built their data warehousing strategy, what they look for from vendors, what advice they have for other companies that are rethinking their data management strategy and have growing data sets, etc. (All questions will be provided prior to the taping)
10 minutes – Audience questions
Abstract:
It’s no surprise that data is growing faster than ever before. Although successful enterprises have embraced analytics as a critical component of their day-today strategy, they were blind-sided by the price tag associated with storing and analyzing these growing data sets. In order to build a sustainable data management strategy for the future, organizations are now looking at next-generation data warehousing solutions that can economically scale from terabytes to petabytes while providing improved performance for BI analytic tools. With all of the data warehousing options available, where do companies start? In this power briefing, featured speaker Jim Kobielus, Sr. Analyst at Forrester Research, will discuss the need for companies to build a longterm data management strategy and the critical factors they should look for when committing to a data warehouse platform. In addition, Jim will talk to expert, Pat Richards, Fox Interactive Media. Pat has successfully implemented a data management strategy for a company that uses “big data” to run their business and will offer up insight from his extensive knowledge about the process. Hear first hand of the requirements he had, the challenges he needed to overcome and how he ultimately built his data warehouse platform.