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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. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    The primary key of a fact table is usually a composite key that is made up of all of its foreign keys. Fact tables contain the content of the data warehouse and store different types of measures like additive, non-additive, and semi-additive measures.

  4. 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.

  5. 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]

  6. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    Dimensions can define a wide variety of characteristics, but some of the most common attributes defined by dimension tables include: Time dimension tables describe time at the lowest level of time granularity for which events are recorded in the star schema; Geography dimension tables describe location data, such as country, state, or city

  7. Database model - Wikipedia

    en.wikipedia.org/wiki/Database_model

    A data warehouse can contain multiple dimensional schemas that share dimension tables, allowing them to be used together. Coming up with a standard set of dimensions is an important part of dimensional modeling. Its high performance has made the dimensional model the most popular database structure for OLAP.

  8. Equinix (EQIX) Q4 2024 Earnings Call Transcript - AOL

    www.aol.com/equinix-eqix-q4-2024-earnings...

    Ease of connectivity and access to data stored in the cloud is a key requirement for inferencing use cases and training workloads. ... the sizable investment in warehouse capital to support our ...

  9. Enterprise bus matrix - Wikipedia

    en.wikipedia.org/wiki/Enterprise_bus_matrix

    The bus matrix purpose is one of high abstraction and visionary planning on the data warehouse architectural level. By dictating coherency in the development and implementation of an overall data warehouse the bus architecture approach enables an overall vision of the broader enterprise integration and consistency while at the same time dividing the problem into more manageable parts [2 ...