The data lake was a critical concept for companies looking to put information in one place and then tap it for business intelligence, analytics and big data. But the promise never quite played out.

I work at a startup and our data is very messy at the moment, as you might imagine. We have a few product level transactional databases, but no central database to store it all in a useful way for ...

What if the very foundation of your organization’s data strategy was holding you back? For years, data lakes have promised flexibility and scalability, yet many businesses find themselves grappling ...

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Machines and the internet are woven into the fabric of our society. A growing number of users, devices and applications work together to produce what we now call “big data”. And this data helps drive ...

"A data lake allows you to apply a schema when you write the data versus a data warehouse that requires you to do a schema on read. So, essentially, a data warehouse requires you to model the data ...

Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping a toe: Integrating a legacy data warehouse into a data lake leverages the structured systems that have been ...

Atlassian is introducing two new capabilities to the Atlassian platform, offering the Atlassian Data Lake and Atlassian Analytics. The Atlassian Data Lake contains cross-product and cross-instance ...

Metadata is information that describes other data. When appropriately used within a data lake, it acts as a tagging system that enables people to search for different kinds of data. Metadata can also ...