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  2. 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 ...

  3. Data mart - Wikipedia

    en.wikipedia.org/wiki/Data_mart

    Data Warehouse and Data Mart overview, with Data Marts shown in the top right.. 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]

  4. Staging (data) - Wikipedia

    en.wikipedia.org/wiki/Staging_(data)

    In other cases data might be brought into the staging area to be processed at different times; or the staging area may be used to push data to multiple target systems. As an example, daily operational data might be pushed to an operational data store (ODS) while the same data may be sent in a monthly aggregated form to a data warehouse.

  5. Lake Havasu - Wikipedia

    en.wikipedia.org/wiki/Lake_Havasu

    Lake Havasu (/ ˈ h ɑː v ə s uː /) is a large reservoir formed by Parker Dam on the Colorado River, on the border between San Bernardino County, California, and Mohave County, Arizona. Lake Havasu City sits on the Arizonan side of the lake with its Californian counterpart of Havasu Lake directly across the lake.

  6. 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]

  7. 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 ...

  8. 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 ...

  9. Dimension (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Dimension_(data_warehouse)

    A common data warehouse example involves sales as the measure, with customer and product as dimensions. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product. A dimensional data element is similar to a categorical variable in statistics.

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