The Death of the Enterprise Data Warehouse

Sponsored, Regent Parlor (NY Hilton)
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Virtualized, scalable, powerful in-memory analytical engines will become the BI cornerstone for the future. The EDW is hemmed in by process and complexity; Hadoop is the upstart that consumes all data but does not readily support non-technical business user’s queries – just try plugging your BI software of choice into Hadoop. Both worlds can co-exist and benefit one another through intermediary high-performance, scalable in-memory, virtualized analytical platforms that provide the new business cornerstone for BI and analytics with minimal effort and investment.

This session is sponsored by Kognitio

Photo of Paul Groom

Paul Groom


Mr. Groom is responsible for the Kognitio Analytics Center of Excellence, a group that includes some of the world’s finest experts in business analytics, data warehousing and business intelligence. In this role, Paul leads the pre-sales technical consulting team and is crucial to the development of Kognitio as a fully-integrated analytical platform. Paul has over twenty years’ experience working with Very Large Databases (VLDBs) with in depth knowledge of databases and data warehouse technologies. He began his career on a database research project at the UK national mapping agency, Ordnance Survey, followed by five years as a Lead Systems Engineer providing pre- and post-sales technical support in the UK and Europe within the then-leading vendors of database machines: Britton Lee (ShareBase), and Teradata/NCR.

In the years since Paul joined Kognitio, he was a key player in the launch of the MPP software with a flexible delivery model (Cloud, Appliance, Software). Having joined as a consultant, he worked his way through various client-facing positions including UK and US Support Management. He spent number of years scaling out the WhiteCross database appliance systems and associated support structure, while on assignment to the US for the company. It was there that he worked extensively on some of the first web analytics and data mining tools as the internet took over American business and retailing in the early 2000s.


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