data lake

A data lake is used to store large and very large amounts of data, with the data first being stored in raw format in a repository. Data lakes are suitable for Big Data analysis. Only when the data is used in an application is it converted into the appropriate data format.

Just like data warehouses, large amounts of data can be stored in data lakes. Which concept is used is a question of cost. While data warehouses store data hierarchically in files and folders, data lakes work with an extremely flat storage architecture. Structured and unstructured, coded and uncoded, unformatted and non-validated data can be stored in a data lake. The data structures are undefined until they are needed.

In the data lake, the data is stored unprocessed, uniquely tagged and tagged with metadata. Storage is therefore less expensive than in data warehouses, where data is stored in files and folders. During data analysis and compilation, only the tags with the metadata need to be searched for relationships. Users can access the data lake via various user interfaces and compile their data.