Power BI Tutorial: How to Use RELATED & LOOKUP

Power BI excels at analyzing data across multiple tables, and two key functions empower this functionality: RELATED and LOOKUP. This tutorial equips you to navigate relationships and extract specific data points based on conditions, unlocking rich insights from your data.

Step 1: Understanding Relationships

• Foreign and Primary Keys: Each table should have a unique identifier (primary key) and a column linking it to another table (foreign key). Establish relationships between tables based on these shared columns.

Step 2: RELATED – Extracting Related Data

• Imagine analyzing sales data with product and customer tables. You want to see the customer name related to a specific product sale.
• Use RELATED to access data from a related table based on the current row’s context.
• Example: RELATED('Customers'[Customer Name]) fetches the customer name related to the current product sale (assuming a relationship exists between product and customer tables).

Step 3: LOOKUP – Extracting Specific Values

• Want to analyze sales performance by region, but your region data exists in a separate table? LOOKUP to the rescue!
• LOOKUP searches for a specific value in a designated table based on a search condition and returns a corresponding value from another column.
• Example: LOOKUPVALUE('Regions'[Sales Performance], 'Regions'[Region Name], SELECTEDVALUE('Products'[Region])) finds the “Sales Performance” value for the currently selected region (assuming appropriate relationships and columns).

Step 4: Advanced Scenarios

• Multiple LOOKUP arguments: Find values based on multiple criteria by stacking LOOKUP arguments.
• Dynamic filters: Use slicers or other filters to dynamically adjust LOOKUP and RELATED results.
• CALCULATE function: Combine RELATED and LOOKUP within CALCULATE for complex calculations involving related data.