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There's a good chance you've already heard the term "data lake."
It's a way to gather large amounts of unstructured and semistructured data into a shared resource which is used by one or more applications and data analysis tools – including very high-end data analytics.
In the world of big data, where vendors try to differentiate themselves with a wide range of marketing terms, data lake may seem like just another buzz phrase. But the concept offers a significantly different way to deal with collected data.
Data lakes have gained mind-share thanks to the rise of Apache Hadoop, the open-source software framework created to handle distributed storage and distributed processing of Big Data – via computer clusters. Other architectures can use data lakes too, but as Hadoop has spread, more IT architects have discovered that they can leverage the technology to change the way they import and store data sets.

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