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  2. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    The snowflake schema is in the same family as the star schema logical model. In fact, the star schema is considered a special case of the snowflake schema. The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. [3]

  3. Aggregate (data warehouse) - Wikipedia

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

    An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a ...

  4. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    In computing, the star schema or star model is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. [1] The star schema consists of one or more fact tables referencing any number of dimension tables .

  5. Database schema - Wikipedia

    en.wikipedia.org/wiki/Database_schema

    The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).

  6. Anchor modeling - Wikipedia

    en.wikipedia.org/wiki/Anchor_Modeling

    Unlike the star schema (dimensional modelling) and the classical relational model (3NF), data vault and anchor modeling are well-suited for capturing changes that occur when a source system is changed or added, but are considered advanced techniques which require experienced data architects. [2]

  7. Schema matching - Wikipedia

    en.wikipedia.org/wiki/Schema_matching

    Approaches to schema integration can be broadly classified as ones that exploit either just schema information or schema and instance level information. [4] [5] Schema-level matchers only consider schema information, not instance data. The available information includes the usual properties of schema elements, such as name, description, data ...

  8. Dimension (data warehouse) - Wikipedia

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

    History is limited to the number of columns designated for storing historical data. Type 4 (Add history table): One table keeps the current value, while the history is saved in a second table. Type 5 (Combined Approach 1 + 4): Combination of type 1 and type 4. History is created through a second history table.

  9. SQL/Schemata - Wikipedia

    en.wikipedia.org/wiki/SQL/Schemata

    The SQL/Schemata, or Information and Definition Schemas, part of the SQL standard is defined by ISO/IEC 9075-11:2008. SQL/Schemata defines the information schema and definition schema , providing a common set of tools to make SQL databases and objects self-describing.