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- The main differences between data warehouse and data lake are12345:
- Data warehouse stores structured data that has been treated and transformed for specific purposes, while data lake stores raw data of all structure types.
- Data warehouse defines the schema before data is stored, while data lake defines the schema after data is stored.
- Data warehouse is used for querying and analyzing data for strategic use, while data lake is used for storing data for a wider and more current scope.
- Data warehouse requires less programming and data science knowledge to use, while data lake requires more data engineering and data science skills to set up and maintain.
Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.Data lake vs. data warehouse: Key differences Data lakes, much like real lakes, have multiple sources (rivers) of structured and unstructured data that flow into one combined site. Data warehouses are designed to be repositories for already structured data to be queried and analyzed for very specific purposes.www.coursera.org/articles/data-lake-vs-data-wareh…While a data lake holds data of all structure types, including raw and unprocessed data, a data warehouse stores data that has been treated and transformed with a specific purpose in mind, which can then be used to source analytic or operational reporting.azure.microsoft.com/en-us/resources/cloud-comput…Data Lake is a storage repository that stores huge structured, semi-structured, and unstructured data, while Data Warehouse is a blending of technologies and components which allows the strategic use of data. Data Lake defines the schema after data is stored, whereas Data Warehouse defines the schema before data is stored.www.guru99.com/data-lake-vs-data-warehouse.htmlA data warehouse is often considered a step "above" a database, in that it's a larger store for data that could come from a variety of sources. Both databases and data warehouses usually contain data that's either structured or semi-structured. In contrast, a data lake is a large store for data in its original, raw format.redpanda.com/blog/database-data-lake-data-wareh…Data warehouses require a lower level of programming and data science knowledge to use. Data lakes are set up and maintained by data engineers who integrate them into data pipelines. Data scientists work more closely with data lakes as they contain data of a wider and more current scope.www.datacamp.com/blog/data-lakes-vs-data-wareh… - People also ask
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WEBApr 26, 2024 · The key differences between a data lake and a data warehouse are as follows [ 1, 2 ]: To gain a deeper introduction to data lakes, check out this video from …
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