BETTER INCORPORATE UNSTRUCTURED DATA INTO YOUR OVERALL ANALYSIS APPROACH
IF YOUR COMPANY currently uses or is looking to use big data and analysis technologies, then there’s a good chance you have heard the term “data lake” in recent months. The technology is so new, however, that analysts and experts on each side of the data lake coin are trying to determine whether the technology is a viable option for enterprises. Although some analysts say data lakes aren’t as beneficial as vendors and stakeholders in the market say they are, there is a chance that, with proper implementation, many companies could use data lakes for storing big data.
Filling In The Gaps At its very core, a data lake is a data repository like any other, which means you can compare it to your other everyday databases and enterprise data warehouses and get a general understanding of how it works. However, data lakes are primarily deWhat Are Data Lakes? BETTER INCORPORATE UNSTRUCTURED DATA INTO YOUR OVERALL ANALYSIS APPROACH signed for storing unstructured and semi-structured data vs. “enterprise data warehouses, which are for storing structured data,” says Daniel Ko, senior consulting analyst at Info-Tech Research Group.
Data lakes take advantage of low-cost Hadoop cluster storage, and for that reason, companies can use them as repositories for data they aren’t using presently but may need to access in the future. “It’s almost like an insurance policy . . . and in the case of a data lake, you are storing some unused data and hoping that one day you will be leveraging it in the future,” Ko says. This allows you to essentially save data for later that you don’t necessarily want to store in your main storage arrays but may want to access in the future