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  2. Data mart - Wikipedia

    en.wikipedia.org/wiki/Data_mart

    A data mart is a structure/access pattern specific to data warehouse environments. The data mart is a subset of the data warehouse that focuses on a specific business line, department, subject area, or team. [1] Whereas data warehouses have an enterprise-wide depth, the information in data marts pertains to a single department.

  3. Data lake - Wikipedia

    en.wikipedia.org/wiki/Data_lake

    Data lakehouses are a hybrid approach that can ingest a variety of raw data formats like a data lake, yet provide ACID transactions and enforce data quality like a data warehouse. [ 14 ] [ 15 ] A data lakehouse architecture attempts to address several criticisms of data lakes by adding data warehouse capabilities such as transaction support ...

  4. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...

  5. Data virtualization - Wikipedia

    en.wikipedia.org/wiki/Data_virtualization

    Some enterprise landscapes are filled with disparate data sources including multiple data warehouses, data marts, and/or data lakes, even though a Data Warehouse, if implemented correctly, should be unique and a single source of truth. Data virtualization can efficiently bridge data across data warehouses, data marts, and data lakes without ...

  6. Spreadmart - Wikipedia

    en.wikipedia.org/wiki/Spreadmart

    A spreadmart (spreadsheet data mart) is a business data analysis system running on spreadsheets or other desktop databases that is created and maintained by individuals or groups to perform tasks that can be done in a more structured way by a data mart or data warehouse. [1]

  7. Data hub - Wikipedia

    en.wikipedia.org/wiki/Data_hub

    A data hub differs from a data lake by homogenizing data and possibly serving data in multiple desired formats, rather than simply storing it in one place, and by adding other value to the data such as de-duplication, quality, security, and a standardized set of query services. A data lake tends to store data in one place for availability, and ...

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  9. Databricks - Wikipedia

    en.wikipedia.org/wiki/Databricks

    Databricks develops and sells a cloud data platform using the marketing term "lakehouse", a portmanteau of "data warehouse" and "data lake". [40] Databricks' Lakehouse is based on the open-source Apache Spark framework that allows analytical queries against semi-structured data without a traditional database schema. [41]