DAX in Power BI offers a range of functions that can be used to manipulate and filter data. Possibly the most confusing among these are DISTINCT and VALUES. While they both return unique values from a column, they differ in their application and also in performance terms and their best use cases. Let's break down these two DAX functions and better understand what makes them distinct.
1. DISTINCT: What It Does and How It Works
DISTINCT returns a one-column table of unique values from the column specified, excluding all the duplicate values. This is most commonly used when one needs to get a clean list of all the different entries within a column.
Output:
DISTINCT returns a table containing the unique values of a column without any duplicates.
It includes rows with BLANK values unless filtered otherwise.
Execution:
Formula Engine: DISTINCT is done by the Formula Engine. Formula Engine requires records from the Storage Engine and does the computation, which also includes filtering, aggregation, and duplicate elimination.
The formula engine, by its nature, works row by row. Therefore, performance tends to be poorer with large volumes of data.
Performance
As DISTINCT works in Formula Engine row by row, performing more checks than VALUES does, it can also be slightly slower on very large models with heavy complex tables.
Depending on the number of duplicates to be removed from the dataset, performance may vary.
Best Use Case:
DISTINCT Use it when working with bigger data models when you want explicitly to suppress duplicates.
This may include creating tables or lists of distinct customers, products, or transactions for further analysis.
2. VALUES: What It Does and How It Works
VALUES returns a one-column table of unique values from a column. However, VALUES is truly contextual, and its behavior changes depending on the context. Unlike DISTINCT, VALUES may return a BLANK value when the data context is empty, which makes VALUES more versatile in certain dynamic situations.
Output:
VALUES returns a table of distinct values of column. If no rows exist in the column, it returns an empty table or returns exactly one BLANK depending upon the context where it is used.
The difference is that VALUES returns a BLANK row when there is no context.
Execution:
Storage Engine: Other than DISTINCT, the main functions of VALUES operate in the Storage Engine. The Storage Engine operates on compressed data and is responsible for fetching the raw data from the data model.
By design, the Storage Engine's purpose is to fetch data fast and execute queries quickly, so VALUES is typically more performant, especially on larger datasets.
Performance:
VALUES, relying on the Storage Engine, is, therefore faster compared to DISTINCT in most situations, particularly if data volume becomes huge. The Storage Engine does bulk operations way more efficiently.
On models with large volumes of data, VALUES can be faster and more resource-efficient than DISTINCT.
Best Case Use:
VALUES should be utilized when you need to return unique values and, simultaneously, capture data context and blank rows where applicable.
That makes it perfect to use within calculated columns and measures, and dynamic contexts in which capturing the current state of a data set is critical.
Another good use case for VALUES relates to relationship management between tables in your data model where the presence or absence of rows in context is important.
3. Basic Differences between DISTINCT and VALUES
| Aspect | DAX Function: DISTINCT |
DAX Function: VALUES |
|---|---|---|
| Output | Returns a unique list of values, including any BLANK values present. |
Returns distinct values. Additionally, it may return a BLANK row when the current context contains no data. |
| Performance | Generally efficient, but may use more memory if working with large datasets containing many BLANK values. |
Similar performance to DISTINCT but context-dependent behavior may require more computational resources in specific cases. |
| Execution (Formula Engine vs. Storage Engine) | Typically evaluated by the Storage Engine (Vertipaq) for most efficient scenarios. However, in complex expressions, it may trigger the Formula Engine. | Like DISTINCT, it is mostly processed by the Storage Engine unless the query context is more complex, where it could invoke the Formula Engine. |
| Best Use Case | Use when you need to return distinct values from a column without any special context considerations. | Use when you want a list of distinct values, but need to account for contexts where no data is present, as it can return a single BLANK value in such cases. |
4. When to Use DISTINCT vs VALUES
DISTINCT:
Best if you just want to remove duplicates and get a unique list of values.
Suitable for summarizing large datasets into smaller sets for further aggregation or reporting.
Usage in cases when the presence of BLANK rows is insignificant or deliberately removed.
VALUES:
More context-sensitive; when the data model has to consider the BLANK values and the dynamic states of the data.
Excellent for complicated scenes that need to understand what is going on currently, like filtering or table relationships.
Used to capture the presence of BLANK rows in data, and when performance is at an absolute premium.
Conclusion: Which One Should You Use?
DISTINCT and VALUES are both strong functions for unique value retrieval in Power BI, for different purposes, though, and their performances are distinct as well. If performance and context sensitivity is a matter, normally VALUES would be better, using Storage Engine running much faster than DISTINCT. However, if you want to remove only duplicates from your dataset and you don't care about the context of those data, it's easier and more effective with DISTINCT. Knowing when to use which function will seriously help you in creating more efficient and accurate Power BI models. Sometimes performance, sometimes output, and even how formula execution may make a huge difference in the efficiency of your data models.
These functions will help in mastering the data transformation to create strong reports that handle unique values intelligently in Power BI.
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