Introducing Data Lakes for Conversational Data
Companies that leverage their conversational data today will quickly outpace competitors. Introducing Airy Conversational Data Lakes: Enabling your company to store and utilize conversational data.
Essentially, data lakes are a place to store all of your data for analytical purposes, much like a data warehouse. The easiest way to differentiate the two, is that a data lake does not include the means to do any sort of calculations with it. It is nothing more than a very reliable and infinitely scalable object store. The benefit of that, is that you only pay for the storage you use. Unlike a data warehouse, where you either pay for empty hard disks or idling server resources.
Meanwhile with a data lake, where storage and compute is decoupled, you can leverage the unstructured nature of data lakes and import data in any shape, volume or form. Furthermore, you can choose to enable crucial features by ticking a few boxes, like encryption and data livecycle policies, for when you want to save even more money on less frequently accessed slices of your data.
But, because storage alone doesn’t provide any insights, data lake providers have worked hard to integrate well with the existing analytics solutions out there, enabling customers to use the tools they are already familiar with, like SQL and Apache Spark.
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