By addressing key challenges such as inconsistent quality control, inadequate documentation, and resource-intensive testing, ...

As enterprises generate and process vast amounts of data, the need for scalable, cost-efficient, and high-performance data ...

And before that data is ready for analysis, it needs to be combined, cleaned, and normalized—a process otherwise known as extract, transform, load (ETL)—which can be laborious and error-prone.

Vikas Nelamangala emphasizes the transformative impact of data federation and virtualization on the digital landscape, ...