Define 'data lake.'

A data lake is a storage repository that holds vast amounts of raw data in its native format. This characteristic means that it can accommodate all types of data – structured, semi-structured, and unstructured – without requiring prior processing or organization. The native format is preserved, allowing for flexibility in how the data can later be analyzed, processed, or transformed. This capability is particularly beneficial for organizations that need to store large volumes of diverse data and intend to apply various analytics techniques at different times, enabling data scientists and analysts to utilize the raw data as needed.

In contrast, a storage repository for structured data only would limit the types of data that can be stored and processed, making it less versatile than a data lake. A platform for data visualization and reporting does not focus on data storage itself but rather on how data is presented and interacted with, which is a different function. Lastly, a database that requires fixed schemas before storing data implies a rigid structure that does not allow for the flexibility and scalability offered by data lakes, where data can be ingested without a predefined format or structure.