Fact Tables Vs. Dimension Tables: Power BI

In Power BI, fact and dimension tables play a crucial role in organizing and analyzing data. With a clear understanding of the difference between these two types of tables, you can build an effective data model and make more informed business decisions from your data.

In this article, we’ll start by establishing a solid understanding of fact and dimension tables and then explore the differences between them.

What Is a Fact Table?

A fact table serves as the central table in your data model. This table holds foreign keys that reference primary keys in your dimension tables. Each foreign key corresponds to specific primary key values in a dimension table.

Fact tables can also contain numeral data you can use to perform calculations within your analysis. Such calculations help with making informed business decisions. For instance, you can include sales orders and log tables in a fact table.

What Is a Dimension Table?

Dimension tables contain data that provide context and descriptions to fact tables. These tables are typically smaller than the fact table and contain primary keys as well as distinct item values. Primary keys are specific items that allow for the unique identification of each row in your table.

For instance, you might have a dimension table that includes product names and their labels, the data table for your Power BI model, store locations, or even pin codes.

Difference Between Fact Tables and Dimension Tables

Fact and dimension tables differ in more ways than just their size. Here are the key difference between the two tables:

1. Regarding the data they contain, fact tables provide information about the granularity of the data, such as daily sales at a store. In contrast, dimension tables offer context about the fact table data. For example, information about the customer making the purchases.
2. Fact tables are the foundation of your data analysis metrics, such as the total daily sales. The dimension tables complement this and serve as useful filters. For instance, you can use them to determine if sales are evenly spread between the stores or if they come from only 70% of them.
3. Fact table lack hierarchy. Dimension tables, however, have a hierarchy. For example, the customer dimension table can link to lower levels with details like names, emails, and phone numbers.
4. Primary keys in fact tables are mapped as foreign keys to dimensions. However, each dimension table has a distinct primary key uniquely identifying each record.

Fact Tables and Dimension Tables Are Important

Clearly defining the difference between fact and dimension tables in Power BI is crucial in building an effective data model. Understanding the distinctions between the two will also help you decide which table best suits data aggregation and which is best for filtering.

A solid grasp of Power BI’s various components can make all the difference in your data analysis.