But there are many other ways to process data besides SQL, and there is a strong demand for different data storage patterns and query mechanisms that optimize the delivery of insight from that raw ...

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

Data quality is paramount in data warehouses, but data quality practices are often overlooked during the development process.

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.

Most solutions require a separate data storage for transformation, although some vendors are using a temporary storage approach. This approach involves caching, querying, validating, and manipulating ...

Oracle Corp. early today debuted a new version of its Autonomous Data Warehouse platform that promises to simplify enterprise analytics projects, as well as reduce costs. Companies use the ...

First, there was a data warehouse – an information storage architecture that allowed structured data to be archived for specific business intelligence purposes and reporting. The concept of the ...

At the 2nd Annual Semantic Layer Summit, which took place April 26, AtScale founder and CTO Dave Mariani sat down with Bill Inmon, recognized by many as the father of the data warehouse, to discuss ...

Has the traditional data warehouse finally reached the end of its life? If so, what will follow it? Will it be a hybrid? We find out.

In the digital transformation of the manufacturing industry, a certain manufacturing enterprise has long faced the dual ...