Guessing is not a strategy: How to build decision velocity with AI and real-time data
June 10, 2026 | Live Webinar
The Modern Data Warehouse
You don’t hear as much that’s new about data warehousing these days. Most companies have their large Teradata, Oracle or DB2 data warehouses that they built in the late 1990s, and some augmented them with more sophisticated OLAP or reporting tools in the mid 2000s.
Most data warehouses in production today are like those homes your parents bought in the 1970s. They may have gone through a kitchen remodel over the past 30 years, but not much else. Most parents are content with old dishwashers, no garbage disposal or basement laundry, but their children certainly want the latest in modern day amenities. Data warehousing users are the same way. While the COBOL-crunching, mainframe-processing baby boomers who built the first data warehouses may have been content with overnight batch jobs to ready information for a data warehouse, the new users of today believe in the adage of real-time information at your fingertips anytime, anywhere.
I have had heard many a story of business users who have returned from conferences where newer vendors in the space like HP Neoview, Netezza and DATAllegro have wowed audiences with advanced analytics and instant processing. After that ensues the familiar finger pointing at IT, asking them why they are using an outdated XYZ data warehouse system. The problem is that data warehouses have largely worked over the past five …
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