The data lake and the data warehouse are two types of data storage.
Their main distinction lies in the structure of the data they contain. A data lake generally stores raw, untransformed data. A data warehouse, on the other hand, stores transformed and cleaned data.
A data lake and a data warehouse are also distinguished by the nature of the data they contain. The raw data of a data lake is data whose purpose is still undetermined. The transformed data in a data warehouse has already been used for a specific purpose within the company.
Another difference between a data lake and a data warehouse is that they are not intended for the same users: the raw data of a data lake requires the expertise of a data scientist to be understood and used, while the structured data of a data warehouse is accessible to non-specialists.
Finally, the data lake and the data warehouse differ in their accessibility and ease of use. The data lake is easier to consult and modify because it is unstructured. On the other hand, the data warehouse is more rigid to manipulate.