3 Best Practices for Data Lake Deployment

3 Best Practices for Data Lake Deployment

3 Best Practices for Data Lake Deployment

Companies vary in their approach to Data Management. Some enterprises collect only a few types of data, thus the traditional data warehouse technique works quite well. For others, expanding sources from which they retain data is forcing them to change their viewpoint, and they’ve moved over to collecting all of their data into the Data Lake.

The benefits of the Data Lake approach are numerous, and as data volumes continue to expand, companies are increasingly realizing the need for a more agile and unstructured way to manage enterprise data. Enter the Data Lake, a technology usually associated with the Hadoop platform that has taken the enterprise world by storm, with many of the top companies in the world investing. Data Lakes typically have very few to no regulatory functions, meaning that any size or scope of data can be collected.

For those organizations beginning their search for Data Lake management and governance solutions, these are the top three best practices we recommend for getting started:

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Deploying Data Governance, as you can probably imagine, is no picnic. Initially, companies must be prepared for more questions than answers, as there are sure to be challenges to data ownership and lots of inconsistencies across competing departments.



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