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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. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    List the columns that describe each dimension (region name, branch name, business unit name). Determine the lowest level (granularity) of summary in a fact table (e.g. sales dollars). An alternative approach is the four-step design process described in Kimball: [ 1 ] select the business process, declare the grain, identify the dimensions, and ...

  4. Dimension (data warehouse) - Wikipedia

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

    Type 3 (Add new attribute): A new column is created for a new value. 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 ...

  5. Snowflake Inc. - Wikipedia

    en.wikipedia.org/wiki/Snowflake_Inc.

    Snowflake Inc. is an American cloud-based data storage company. Headquartered in Bozeman, Montana , it operates a platform that allows for data analysis and simultaneous access of data sets with minimal latency . [ 1 ]

  6. Help:Advanced table formatting - Wikipedia

    en.wikipedia.org/wiki/Help:Advanced_table_formatting

    For each table, insert an alpha-prefix on each column (making each row-token "|-" to sort as column zero, like prefix "Row124col00"), then sort into a new file, and then de-prefix the column entries. Again, bear in mind, the tedious hand-editing of items in each row is often faster than the potential delay of automated edits gone awry.

  7. 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]

  8. Aggregate (data warehouse) - Wikipedia

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

    Since dimensional models only gain from aggregates on large data sets, it should be considered at what size of the data sets one should start using aggregates One can also ask oneself if a data warehouse always handles data sets that are too large for direct queries, or if it sometimes is a good idea to omit the aggregate tables when starting a ...

  9. Data dictionary - Wikipedia

    en.wikipedia.org/wiki/Data_dictionary

    Here is a non-exhaustive list of typical items found in a data dictionary for columns or fields: Entity or form name or their ID (EntityID or FormID). The group this field belongs to. Field name, such as RDBMS field name; Displayed field title. May default to field name if blank. Field type (string, integer, date, etc.)