While data lakes are often compared to data warehouses, the only thing they have in common is that both are used to store, and later analyze, massive amounts of data. A data lake is considered a vast pool of raw data where the purpose of the data is not defined, while a data warehouse is a repository for structured and defined data that has already been processed for a particular purpose.
In an article recently published by Insider Pro, Michael Knopf, a software engineer here at TruSTAR, helps to break down the pros and cons of utilizing a data lake, what a data lake does, and if a data lake is right for your organization.
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