Now that analyzing data in real time and extracting value from data structures such as text is conceivable, organizations are moving away from the centralized data warehouse. But rather than abandon it completely, businesses are augmenting their infrastructures to match the kinds of data they're working with, according to Shawn Rogers, vice president of research in business intelligence (BI) and data warehousing for Enterprise Management Associates (EMA) in Boulder, Colo.
Rogers and his EMA colleagues have dubbed this trend the hybrid data ecosystem. Other analysts refer to it as the logical data warehouse or the extended data warehouse.
"I don't want anyone to misunderstand me," Rogers said. "The data warehouse will continue to be a huge part of our data ecosystem and will continue to provide critical value for us. But, with that said, there is a movement for matching data and platforms and workloads for the best possible outcomes."
During his session at the 11th annual Pacific Northwest BI Summit, Rogers spoke about a confluence of factors driving the need -- and the feasibility -- for a hybrid data ecosystem.
"There are three or four drivers that are undeniable," he said. "It's making huge changes in our infrastructure and the way we manage information."
With data spread out to different platforms, Rogers, who presented alongside Robert Eve, executive vice president for marketing at the data virtualization vendor Composite Software Inc., also highlighted the need for good integration.
In this video interview, recorded at the summit in Grants Pass, Ore., Rogers spoke with Nicole Laskowski, SearchBusinessAnalytics.com's news editor, about his presentation on the hybrid data ecosystem and data integration.
In this video, viewers will learn about:
- How to define the hybrid data ecosystem
- The factors that are driving the hybrid data ecosystem
- Why data virtualization could come in handy when managing a hybrid data ecosystem
- Tips on how to expand the data warehouse