Three examples to make you understand the design of data warehouse multidimensional data model

I. Overview

Multidimensional data model is the most popular data model of Data Warehouse, the most typical data pattern of multidimensional data model includes star pattern, snowflake pattern and fact Constellation pattern, this article shows the pattern and difference of the three examples.

Two, star schema (star schemas)

The core of the star pattern is a large central table (fact table), a small set of subordinate tables (dimension tables). Examples of star patterns are as follows:

Three, snowflake mode (snowflake schema)

Snowflake mode is an extension of the star schema, where some dimension tables are normalized and further decomposed into additional tables (dimension tables). The snowflake pattern is shown in the following example:

We can see that the Address table is further subdivided into the city dimension. The Supplier_type table is further subdivided into supplier dimensions.

The fact Constellation pattern (fact constellation) or Galaxy schema (Galaxy Schema)

A data warehouse consists of several topics, including multiple fact tables, which are public and shareable, which can be seen as a collection of star patterns, and thus referred to as Galaxy patterns or fact constellation patterns. This pattern is shown in the following example:

As shown, the fact constellation pattern contains two fact tables: Sales and shipping, both of which share a dimension table.

V. Summary

The fact constellation pattern is the longest-used data pattern in the data warehouse, especially for enterprise-level data warehouses (EDW). This is also a typical feature of data warehouse, which is different from data mart, and fundamentally, the model of data Warehouse data model is more to avoid redundancy and data reuse , and to apply out-of-the-box mode is the most reasonable choice for designing Data warehouse. Of course, under the big Data technology system, the design of data warehouse data model is still a blind spot to explore.

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Three examples to make you understand the design of data warehouse multidimensional data model