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 ...

In the ongoing debate about where companies ought to store data they want to analyze – in a data warehouses or in data lake — Databricks today unveiled a third way. With SQL Analytics, Databricks is ...

Think about the term “data warehouse”: it conjures up images of days long gone by when IT organizations were primarily concerned with packing up all their digital stuff into standard-sized boxes and ...

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 ...

Organizations that really want to take advantage of a higher performance, more agile and lower cost data warehouse architecture, should implement master data management (MDM) to improve data quality.

Now that we’re emerging from the pandemic and the dust is starting to settle, organizations are taking a good, hard look at their digital transformation and modernization priorities moving forward. To ...

The rise of “data mesh” as a buzz phrase in the data management world has generated significant interest, but is it the right approach for your organization? While data mesh has its proponents, many ...

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 ...

It’s felt obvious for some time that, as an industry, we’ve been trying to shove square data warehousing tools into round, data-driven application holes. But it wasn’t until I read Decodeable CEO Eric ...