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Is your data warehouse becoming too restrictive for all the information your company is now looking to capture? If so, it may be time to make the jump to a data lake. But first, make sure you know what to expect from a data lake deployment.
A data lake is a form of big data architecture that can store a mix of data, both raw data and data sets filtered for specific analytics applications. The data lake format offers more flexibility in storing and managing data for analytics projects than traditional data warehouses do.
However, it also comes with its own set of challenges that complicate the data lake implementation process and make maintenance and governance an ongoing operation. Finding a balance between regulating the data lake and keeping it wide open for analytics uses is one of the most important considerations for a successful deployment.
Are you ready to set sail on a data lake implementation at your company? Take this short quiz to find out how much you know about data lakes, and get links to some additional articles to help guide you.
More on why data governance in a big data environment is so important
Read about how Hadoop helped enable a data lake at Allstate Insurance
Why it can be useful to test out your data lake before a full implementation