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  2. Unstructured data - Wikipedia

    en.wikipedia.org/wiki/Unstructured_data

    Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text -heavy, but may contain data such as dates, numbers, and facts as well.

  3. Data at rest - Wikipedia

    en.wikipedia.org/wiki/Data_at_Rest

    Data at rest in information technology means data that is housed physically on computer data storage in any digital form (e.g. cloud storage, file hosting services, databases, data warehouses, spreadsheets, archives, tapes, off-site or cloud backups, mobile devices etc.). Data at rest includes both structured and unstructured data. [1]

  4. Operational data store - Wikipedia

    en.wikipedia.org/wiki/Operational_data_store

    An operational data store (ODS) is used for operational reporting and as a source of data for the enterprise data warehouse (EDW). It is a complementary element to an EDW in a decision support environment, and is used for operational reporting, controls, and decision making, as opposed to the EDW, which is used for tactical and strategic decision support.

  5. Operational database - Wikipedia

    en.wikipedia.org/wiki/Operational_database

    Since the early 1990s, the operational database software market has been largely taken over by SQL engines. In 2014, the operational DBMS market (formerly OLTP) was evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines, as well as XML databases and NewSQL databases.

  6. Business intelligence - Wikipedia

    en.wikipedia.org/wiki/Business_intelligence

    According to projections from Gartner (2003), white-collar workers spend 30–40% of their time searching, finding, and assessing unstructured data. BI uses both structured and unstructured data. The former is easy to search, and the latter contains a large quantity of the information needed for analysis and decision-making.

  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 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 ...

  9. Spreadmart - Wikipedia

    en.wikipedia.org/wiki/Spreadmart

    In the rest of the article Stephen Samild argues that a spreadmart fulfills a number of roles that a data warehouse cannot fulfill as easily or as cheaply due to the lack of integration with unstructured data, the lack of read-write capabilities, the long time span needed for integration of new sources in the data warehouse and the inherent ...