The "data" part of the terms "data lake," "data warehouse," and "database" is easy enough to understand. Data are everywhere, and the bits need to be kept somewhere. But should they be stored in a ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Database vs Data Warehouse vs Data Lake comes down to how data is stored, processed, and used. A database is typically built for transactional work with live, detailed data stored in tables, while a ...

A data warehouse is a repository of data from an organization's operational systems and other sources that supports analytics applications to help drive business decision-making. Data warehousing is a ...

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 ...

If you’re looking for a quick and easy way to leverage ana­lytics focused on a specific topic, look no further. During his BLUEPRINT 4D session, Patrick Wheeler, product management, Oracle Database, ...

Numerous options exist for buying a data warehouse platform. Although evaluating them need not be a complicated process, taking the appropriate steps will help to ensure that you invest in the best ...

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 ...

The system is based on server hardware from Sun Microsystems, which Oracle is in the process of acquiring for $7.4 billion. That apparently leaves Hewlett-Packard, which provided the hardware for the ...

Now that data warehousing has become ubiquitous in the corporate world, "clean slate" designs of entirely new decision support systems are becoming somewhat rare. Instead, designs and roadmaps are ...