Data lakes and data warehouses are widely used for storing big data, but they are not interchangeable terms. A data lake is a vast pool of raw data, the purpose for which is not yet defined. A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose. The two types of data storage are often confused but are much more different than they are alike. The only real similarity between them is their high-level purpose of storing data. The distinction is important because they serve different purposes and require different eyes to be properly optimized. Thus, while a data lake works for one company, a data warehouse will better fit another.