Everything to Know About Fact Tables for Data Warehousing

When creating a new data warehousing environment, there is much to consider. One of the most important elements to be aware of is the fact table. The fact table is one of the central tables within a data warehouse that uses a star schema. There are three main types of fact tables, each of which will store a different set of information to be analyzed and used as part of an overall business intelligence strategy.

Types of fact tables in an enterprise data warehouse

When setting up a data warehouse, you will need to establish the fact tables used for organizing and accessing the data. In general, there are three main types of fact tables that most organizations will have set up:

  • Transactional – A transactional fact table is going to have one line for each piece of data associated with a transaction. This will usually have the most details, or grains, which means it will have the largest number of dimensions.

  • Periodic snapshots – A periodic snapshot fact table is where data is stored that is associated with a snapshot of an environment at a specific moment in time. This allows teams to access information that was originally part of the transactional fact table at a precise point in history.

  • Accumulating snapshots – An accumulating snapshot is used to track activity associated with a business process where there are set start and endpoints. An example of this could be producing a product where snapshots of the related data will be taken at each key point from the beginning of production through to when it is sold.

Each of these fact sheets has a clear type of data that is incorporated into them. When planning out the data integration for your company, it is important not only to ensure data is directed to the right fact table but also that all relevant data is accounted for. While some data sources are obvious, many others can go overlooked if not planned for in an overall enterprise data warehouse strategy. Failing to bring all data together in one place will make data mining and other activities more difficult in the future.

Designing cloud data warehousing systems

When creating a new data warehouse, most companies today choose to do it on the cloud. There are many data warehousing services (DWaaS) that offer cloud-based managed solutions for organizations of all types. While this type of technology will operate the same, whether on-prem or on the cloud, it is important to ensure that the fact tables and other aspects of the environment are properly configured.

Fact table grain and dimensions

When creating a fact table, you need to declare a grain, which describes exactly what a given record on the table represents. Based on what the grain is, establishing dimensions of the table is also important. An example of grain on a transactional fact table would be each item on an invoice: the customer name, address, delivery date, products or services provided, amount paid, and any other related data should each be represented by a grain on the table.

In the examples given, the dimensions of each grain would be established in a way to properly accommodate the data. The dimensions of a grain used to represent a name need to be sufficient to contain the longest potential names that would be included, for example. Once the fact table is properly established, data integration can begin.

Experienced data warehouse consulting

Creating and maintaining a good data warehouse requires a great deal of work as well as a level of expertise that many organizations simply do not have. Trianz offers experienced data warehouse consulting services to help you plan, create, and support your entire data warehousing environment.

We have extensive experience helping companies across nearly every industry and are authorized consultants for every major cloud data warehousing services provider. We will work closely with you to determine your exact needs, set up the required fact table, and ensure everything is configured properly so you can begin using your data warehouse right away.

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