Daily DAX : Day 334 APPROXIMATEDISTINCTCOUNT

APPROXIMATEDISTINCTCOUNT DAX Function in Power BI

What is APPROXIMATEDISTINCTCOUNT?

The APPROXIMATEDISTINCTCOUNT function in DAX (Data Analysis Expressions) is a statistical aggregation function used in Power BI to estimate the number of unique (distinct) values in a specified column. It provides an approximation rather than an exact count, which makes it faster for processing large datasets.

Syntax

APPROXIMATEDISTINCTCOUNT(<column>)
    

• <column>: The column reference (e.g., 'Table'[ColumnName]) containing any data type.

Return Value: An integer representing the approximate distinct count, or BLANK if no rows are found.

How Does It Work?

This function invokes an optimized aggregation operation directly in the underlying data source, reducing query time at the cost of slight accuracy loss (typically up to 2% error with 97% probability). It leverages database-specific functions like APPROX_COUNT_DISTINCT in SQL engines.

Example: For a sales table with a 'ProductID' column:

Unique Products (Approx) = APPROXIMATEDISTINCTCOUNT(Sales[ProductID])
    

If the exact distinct count is 1,000, this might return 980–1,020 for speed gains.

Key Differences from DISTINCTCOUNT

Aspect	APPROXIMATEDISTINCTCOUNT	DISTINCTCOUNT
Accuracy	Approximate (slight deviation)	Exact
Performance	Faster for large data	Slower on big datasets
Use Case	Estimates in reports/dashboards	Precise calculations

Use Cases

Ideal for:

• Large Datasets: Quickly estimating unique customers, products, or sessions in billions of rows without slowing down reports.
• DirectQuery Mode: Works with sources like Azure SQL, BigQuery, Databricks, and Snowflake for real-time queries.
• Performance Optimization: In interactive dashboards where speed trumps exact precision, e.g., monitoring unique website visitors.

Not Suitable For: Scenarios requiring 100% accuracy, like financial audits—use DISTINCTCOUNT instead.

Supported Storage Modes: Import mode (fully) and DirectQuery (on compatible sources).