Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A data warehouse is defined as a central repository that allows ...

AI has been reshaping how operations-heavy companies think about data infrastructure, and it could fundamentally reshape ...

One day, corporations awoke to the fact that having data was not the same thing as having believable data. They awoke to discover the meaning of “data integrity.” That was the day the enterprise data ...

The data warehouse architecture and the data lake design pattern have converged to form a new, richer data architecture, a new report says, and both have already gone mainstream in the cloud.

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More This article was contributed by Gunasekaran S., director of data ...

The data lakehouse – it’s not a summer retreat for over-worked database administrators (DBAs) or data scientists, it’s a concept that tries to bridge the gap between the data warehouse and the data ...

With the majority of DBTA subscribers reporting the existence of budgets for modernizing their data platforms, the widespread demand for greater scalability and agility becomes a difficult task to ...

The major issues of data warehouse architecture are higher cost, lower performance and limited access. The reasons for these problems focus the architectural design. The solutions are proposed with ...

Early adopters want tools, but the bulk of the market wants products. Big data doesn’t change this principle. It is natural that in the early stages the raw power of tools should be celebrated. That ...