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A Better Understanding of Data Lakes

By   /  January 30, 2015  /  No Comments

Mirror Lake, New Zealandby Angela Guess

Jaikumar Vijayan of Datamation recently wrote, “If you’re an enterprise data management professional, there’s a good chance you’ve run across the term ‘data lake’ in recent months. Though it might sound like an esoteric concept, a data lake is simply a repository where enterprises can store data from disparate sources in their original, native formats. Companies these days generate a lot of structured data and unstructured data in the form of multimedia files, telemetry and sensor data, spreadsheets, emails, web logs and system logs. A lot of the data is used. A lot more remains unused and untapped usually because it is too complicated and costly to extract value from it.”

He goes on, “A data lake provides a sort of central destination for all of that data. It allows companies to ingest and store data in any format from any source without having to worry about transforming or structuring it first as is needed with a traditional data warehouse or relational database. (If all that sounds similar to a description of a Hadoop environment, its only because it is. But, more on that in a bit.) The idea behind a data lake is straightforward enough. Instead of placing data into multiple, purpose-built data stores, a company grappling with massive amounts of disparate data can dump everything into a data lake without modification, says Gartner analyst Nick Heudecker.  It offers the perfect landing zone for enterprises to park and integrate all their valuable and untapped data while they figure out what to do with it.”

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