The purpose of a data lake
You might not need a data lake if your company is a bootstrap start-up with a small client base. However, even the smaller entities that adopt the data lake pattern in their data ingestion and consumption will be nimbler than their competitors. Especially if you already have other systems in place, adopting a data lake will come at a high cost. The benefits must outweigh these costs, but this might be the difference between crushing your competitors and being thrust into the pile of failed companies in the long run.
The purpose of a data lake is to provide a single store for all data types, structures, and volumes, to support multiple use cases such as big data analytics, data warehousing, machine learning, and more. It enables organizations to store data in its raw form and perform transformations as needed, making it easier to extract value from data. When you are building a data lake, consider the following five V’s of big data:
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