Introduction
Data is one of the most important assets that an organisation has because it can be used strategically to make sure that an organisation remains relevant to the trends and needs of users. The primary purpose of organising data is to make analysing it easy and get results on the go.
All the decisions that an organisation takes are driven by the analysis done on the data. For example, whenever a company plans to release a new product, it carries out significant research based on data to ensure that it would be successful or not.
It gets really complicated for a tech giant like Google to store a humongous amount of data. To overcome this problem, the concept of data warehousing was introduced. A data warehouse is a central repository of information that can be analyzed to make more informed decisions. Data flows into a data warehouse from different sources and stored for further use.
But the data is of no use if it is messy and unorganised as it can’t be analysed to get concrete results. That’s where the two most popular data warehousing models Star and Snowflake come to the rescue.
In this article, we will discuss Star Vs Snowflake Schema and will also list out the key differences between these two. Let’s get started.
Star Schema
Star schema is one of the simplest data schemas for data warehousing. The structure of the star schema is similar to the structure of the star. In a star schema, a fact table is placed in the center, which references multiple dimension tables that look like a star when arranged in a diagram.
To understand the above definition clearly, we need to know about the following terms.
- Fact table: it is the central table in the star and snowflake schema. All the foreign keys of the associated dimension table are mapped to the fact table.
- Dimension table: a table that describes all the measurements recorded in the fact table. Contains all records that are needed to perform analysis.
It is also known as star join schema and is highly optimised to perform queries on large data sets.
In the above example, we have a fact table fact_sales, and the primary key of the fact_sales table is composite and made by a combination of the foreign key from all five dimension tables. The arrangement of these tables in the diagram resembles a star shape.
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