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  2. Relational data mining - Wikipedia

    en.wikipedia.org/wiki/Relational_data_mining

    Relational data mining is the data mining technique for relational databases. [1] Unlike traditional data mining algorithms, which look for patterns in a single table (propositional patterns), relational data mining algorithms look for patterns among multiple tables (relational patterns). For most types of propositional patterns, there are ...

  3. 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 ...

  4. Data store - Wikipedia

    en.wikipedia.org/wiki/Data_store

    Data store can refer to a broad class of storage systems including: Paper files; Simple files like a spreadsheet; File systems; Email storage systems (both server and client systems) Databases. Relational databases, based on the relational model of data; Object-oriented databases. They can save objects of an object-oriented design. NoSQL ...

  5. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    Collecting data from numerous sources and analyzing it using different data analysis tools has its advantages, including overcoming the risk of method bias; using data from different sources and analyzing it using multiple analysis methods guarantees businesses and organizations robust and reliable findings they can use in decision making.

  6. Data integration - Wikipedia

    en.wikipedia.org/wiki/Data_integration

    Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. [1] There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories).

  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 ...

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  9. 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.

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