To improve performant DAX queries for the Power BI environment, one should incorporate efficient data modeling, appropriate query wording, and embedding of DAX functions. The following are the guidelines:
1. Build an Effective Data Model
Star Schema: A star schema is more efficient than a snowflake schema. Star schemas reduce the number of relationships that the Power BI engine needs to resolve, which enhances performance.
Do Not Allow Relationships Between Tables: These can considerably slow calculation performance. Employing bridge tables or flattening the data would be suitable alternatives to minimize the interconnection.
Use Numerals Instead of Text Wherever Possible: Limit the cardinality. High cardinality will rely on columns set in the relationship, used in slicers and grouping. For instance, instead of texts, use numeric keys.
2. DAX Queries Need To Be Structured Efficiently.
Filter Early: Filter out unnecessary rows at the lowest level in the calculation chain as much as possible. For example, within the scope of this paper, LIMIT CALCULATETABLE… USE CALCULATION TABLE FOR SUBSET INTERMEDIATE PROCESSING. This tactic will help alleviate the amount of data processed.
Use Variables (VAR): Intermediate results should not repeat a calculation inside a query. They can be declared with VAR, thus avoiding a redundant calculation, as the engine only evaluates the variable once.
Avoid the Use of Iterative Functions: Avoid row-based functions such as FILTER, SUMX, or LOOKUPVALUE as much as possible. They should be avoided for aggregating columns rather than performing operations on them since operations on columns are quicker.
Use Measures, Not Calculated Columns
Measures Over Columns: Always use measures and avoid calculated columns unless unavoidable. Measures do not constitute part of the data model, unlike calculated columns, which only take effect when the query is executed.
Power Query Pre-Processing: Where conditional logic needs to be applied, this should be done during data transformation in Power Query instead of DAX by creating calculated columns.
4. Relationship Management
Bi-directional relationships Should Be Discouraged. They can make calculations complex and slow. When bi-directional behavior is needed, it is preferable to use single-direction relationships and explicit DAX functions such as CROSSFILTER.
Controller Inactive Relationships: Instead of using Make all relationships active, which will adversely impact the model's performance, integrate USERELATIONSHIP for selected calculations only.
Advice in General
Improve the Performance of the Calculated Tables: Avoid using DAX to create big calculated tables unless there is no other option; do as much preprocessing as possible in Power Query.
Minimize Data Volume: Add only necessary columns and rows to your model. Use summarized or aggregated values for high reports.
Utilize Performance Analyzer: Find which visuals or measures slow down the Power BI and enhance DAX code based on the Power BI Performance Analyzer.
Enable Query Folding: To avoid processing latency, DirectQuery or Power Query transformations should be performed at the source database.
If these methods are employed, it is possible to enhance the user's enjoyment of the performance and efficiency of DAX queries and Power BI reports.
