How to create Data Models in Power BI | Build efficient data models in Power BI | TrendingTechnology

In this article, we will explore how to construct an efficient data model in Power BI. Before delving into the creation of data models, let's first understand what a data model is in Power BI and why we need data models when working with it.

What is a Data Model in Power BI?

A data model is essentially a representation of data achieved by establishing relationships between multiple tables. Data models primarily consist of two types of tables: FACT Table and DIMENSION Table.

• FACT Table = Data Table (contains numeric values)
• DIMENSION Table = Look-Up Table (contains text values)

To connect these tables, we require keys. Two types of keys are available:

• Primary Key (a unique key to identify each row of the table)
• Foreign Key (contains multiple instances of each value)

By using these keys, we can create relationships between the tables, forming what we call a Data Model. The ultimate goal of creating a data model is to have a structure optimized for reporting and analysis.

How to Build an Efficient Data Model in Power BI

1. Use of Star Schema model over Snowflake Schema: The Star Schema model enhances the cleanliness and organization of the overall model.
2. Avoid bi-directional relationships on tables: Bi-directional relationships can be resource-intensive, so it's advisable to avoid them.
3. Reduce calculated columns: Calculated columns occupy physical column space in tables, so they should be used judiciously.
4. Optimize DAX queries: Employ optimized versions of DAX functions to achieve better performance.
5. Data Cleaning: Conduct data cleaning as an initial step before loading data into the data model. If unnecessary columns still exist, remove them.

These best practices can significantly improve the performance of data models. If you have additional insights or practices to share, feel free to comment below.