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This week, Oracle announced a major extension of its cloud-based Autonomous Data Warehouse service that transforms it into an end-to-end offering with a heavy dose of self-service for business users.

To fit into modern analytics ecosystems, legacy data warehouses must evolve—both architecturally and technologically—to deliver the agility, scalability, and flexibility that business need to thrive ...

Essentially, a data warehouse is an analytic database, usually relational, that is created from two or more data sources, typically to store historical data, which may have a scale of petabytes. Data ...

Lea noted that Teradata has been focusing on an integrated data warehouse stack that includes hardware, software and an optimized database, I/O and memory. "But the real value is that we're 100 ...

eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...

For a data warehouse to deliver near real-time information, the choices generally are to update the warehouse more frequently or access data directly from operational systems. Either way, the push to ...

Enterprise data warehouses, or EDWs, are unified databases for all historical data across an enterprise, optimized for analytics. These days, organizations implementing data warehouses often consider ...

According to Gartner, Inc., CIOs need to familiarize themselves with nine key trends in data warehousing and how they will impact the cost-benefit balance of technology deployed to deliver business ...

Since the 1990s, organisations have gathered, processed and analysed business information in data warehouses. The term “data warehouse” was introduced to the IT mainstream by American computer ...