Keeping data lakes from becoming data swamps.

Posted by Ray Chelstowski on Jun 13, 2022 12:00:00 AM

A data lake is a central storage repository that holds a large amount of raw data for later use. Since data can be stored as-is, your business doesn’t have to waste its effort on converting, structuring, and filing data until it is needed. This allows a data lake to offer much greater flexibility, cost-effectiveness, and scalability.

On the flip side, though, this kind of flexibility can be data lakes’ Achilles heel. An unmanaged data lake can become a “data swamp” if it is used as a dumping ground with poor integrity, poor quality, stewardship, governance, and data protection. In turn, data lakes have historically failed because they often lack any degree of pre-planning. Instead of building their data lakes in accordance with specific needs, organizations were haphazardly dumping data into them, with much of it being useless and unidentifiable. And while the point of a data lake is to eventually have most of your company’s data available to enable a wide variety of analytics, you must balance that with your need to prove the value of the data lake to your business. For raw data to have any use, it must remain explainable at any moment into the future.

At Kognitiv, we help clients establish a data gathering protocol that secures information that is specifically actionable to a particular brand’s business. This loyalty approach puts a customer’s journey at the center of our strategy, and that journey changes by brand. While knowing for example that a customer attended college may be important to many brands, knowing that they majored in economics may matter to only a select few. So, we instead focus on the end game of the capture and storage protocol. This ensures that whatever a brand captures from their customer can be later applied to better engage them and deliver a value proposition that expands their lifetime value.

Lastly, as important as proper capture and analysis is, brands need to put a data governance in place that streamlines these protocols and limits access to the lake to a few key constituents. With data, too many cooks spoil the broth and the lake combined.

The bottom-line is that in a fast-changing world where data has been termed “the new oil” brands need to know what they want to do (or may want to do in the future) with the info they capture and who they want to manage it. Otherwise, they can be assured that it will be impossible to evaluate because it will become buried in a swamp of meaningless fun facts. Those catch-all’s only keep brands from smooth sailing waters, where they can build loyalty that’s “lake-like” and lasting.

Topics: Customer Data & Analytics, Segmentation, Customer Engagement, Personalization


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