What is the difference between DWH and data lake?

Question

Data lakes and data warehouses are both 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.

What is the difference between data lake and database?

What is the difference between a database and a data lake? A database stores the current data required to power an application. A data lake stores current and historical data for one or more systems in its raw form for the purpose of analyzing the data.

Is 201 what is the main difference between a data warehouse and a data lake?

1. Data Structure. Data lakes store data in its unprocessed raw form, allowing faster loading and accessibility by removing the transform process. In contrast, data warehouses store data in its processed form, requiring specific data structures in order to access them.

What is the difference between ODS and data lake?

An ODS doesn't require the same kind of transformations. Instead, data remains in its existing schema. In this sense, ODS is more like a data lake, which uses the schema-on-write approach, although an ODS is much smaller than a data lake (and can only store structured data.)

What is the difference between data lake and data mart?

Data lakes contain all the raw, unfiltered data from an enterprise where a data mart is a small subset of filtered, structured essential data for a department or function. Data marts are very specific, allowing for fast, effective analytics of relevant summarized information.

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