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  2. Snowflake Inc. - Wikipedia

    en.wikipedia.org/wiki/Snowflake_Inc.

    Snowflake Inc. was founded in July 2012 in San Mateo, California, by Benoît Dageville, Thierry Cruanes and Marcin Żukowski.Dageville and Cruanes previously worked as data architects at Oracle Corporation; Żukowski was a co-founder of Vectorwise.

  3. 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]

  4. Data vault modeling - Wikipedia

    en.wikipedia.org/wiki/Data_Vault_Modeling

    Data vault modeling was originally conceived by Dan Linstedt in the 1990s and was released in 2000 as a public domain modeling method. In a series of five articles in The Data Administration Newsletter the basic rules of the Data Vault method are expanded and explained.

  5. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation schema.

  6. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. [2] The star schema gets its name from the physical model's [3] resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points.

  7. 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.

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  9. OLAP cube - Wikipedia

    en.wikipedia.org/wiki/OLAP_cube

    An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [ 2 ] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.

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