Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A data lake is defined as a centralized and scalable storage repository ...

Microsoft Fabric expands as industry analysts reveal critical criteria enterprises need for evaluating AI-ready data ...

Co-authored by Shamnad Mohamed Shaffi of Amazon Web Services, Sunish Vengathattil of Clarivate Analytics, and Jinal Mehta of Amazon, the study explores how a cutting-edge data lakehouse architecture ...

Not all data lakes are created equal. If your organization wants to adopt a data lake solution to simplify and more easily operate your IT infrastructure and store enormous quantities of data without ...

As an industry, we’ve been talking about the promise of data lakes for more than a decade. It’s a fantastic concept—to put an end to data silos with a single repos­itory for big data analytics.

Copies of large datasets tend to proliferate in many organizations because they reside in a data lake that lacks the ability to perform the work necessary to turn that information into business ...

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 ...

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 ...

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