What is a Data Lake?
A data Lake is a centralized storage repository that stores a large amount of data from several sources across many data formats. The data can be structured, semi-structured, and unstructured. It allows storing the data as-is at any scale.
A data lake differs from a data warehouse in the following aspects:
- A data Lake does not have any predefined scheme, which allows it to store the data as-is. Whereas data warehouse is well-defined and structured before storing the data.
- The data in the data lake is quite complex and disorganized due to the availability of data in various formats. It needs an expert to understand the data and their relationships. The data warehouse is in simplified form and is easily accessible due to its well-defined and documented schema.
- Since the data warehouse has a well-defined schema, it takes time and resources to modify the data due to its rigidity. In comparison to a data warehouse, a data lake can adapt to the modifications easily.
What are the benefits of a data lake?
- Enables the data to be stored as-is in any format.
- Due to its schema-on-read principle, it saves a lot of time spent on defining a schema.
- Enables data scientists or analysts to access, prepare, and analyze data faster and with more accuracy.