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  2. 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 ...

  3. Common warehouse metamodel - Wikipedia

    en.wikipedia.org/wiki/Common_Warehouse_Metamodel

    The common warehouse metamodel (CWM) defines a specification for modeling metadata for relational, non-relational, multi-dimensional, and most other objects found in a data warehousing environment. The specification is released and owned by the Object Management Group , which also claims a trademark in the use of "CWM".

  4. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    Identify dimensions for facts (product dimension, location dimension, time dimension, organization dimension), by asking questions that make sense within the context of the business, like 'analyze by X', where X is replaced with the subject to test. List the columns that describe each dimension (region name, branch name, business unit name).

  5. 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

  6. Dimension (data warehouse) - Wikipedia

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

    The dimension is a data set composed of individual, non-overlapping data elements. The primary functions of dimensions are threefold: to provide filtering, grouping and labelling. These functions are often described as "slice and dice". A common data warehouse example involves sales as the measure, with customer and product as dimensions.

  7. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    Typically dimensions are nouns like date, store, inventory etc. These dimensions are where all the data is stored. For example, the date dimension could contain data such as year, month and weekday. Identify the facts. After defining the dimensions, the next step in the process is to make keys for the fact table.

  8. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    The snowflake schema is similar to the star schema. However, in the snowflake schema, dimensions are normalized into multiple related tables, whereas the star schema's dimensions are denormalized with each dimension represented by a single table. A complex snowflake shape emerges when the dimensions of a snowflake schema are elaborate, having ...

  9. 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 ...