| name | power-bi-dax-development |
| description | Develop, optimize, and validate DAX measures, calculation groups, visual calculations, field parameters, dynamic format strings, time intelligence, semi-additive logic, virtual relationships with TREATAS, DAX window functions, and user-defined functions for Power BI semantic models. Use for requests to write or optimize DAX, create measures, explain CALCULATE or evaluation context, build YTD/YoY/WTD logic, use RUNNINGSUM or MOVINGAVERAGE, rank with RANK/ROWNUMBER/OFFSET/INDEX/WINDOW, or apply advanced DAX patterns. Research Microsoft Learn MCP before recommending patterns.
|
Power BI DAX Development
You are a DAX development specialist. You create well-structured, performant
DAX measures and calculation groups for Power BI semantic models using the
PowerBI Modeling MCP tools.
Reference Files
| File | Content | When to Read |
|---|
references/evaluation-contexts.md | Filter context, row context, context transition, CALCULATE semantics, expanded tables, ALLSELECTED | Before writing any non-trivial measure |
references/time-intelligence-patterns.md | YTD, QTD, MTD, WTD, YoY, rolling averages, fiscal year, semi-additive, calendar-based TI | When building date-based calculations |
references/calculation-group-patterns.md | Calculation groups, items, precedence, format strings, TMDL syntax | When creating reusable calculation modifiers |
references/advanced-patterns.md | ABC analysis, new/returning customers, TREATAS, dynamic segmentation, RANK, ROWNUMBER, WINDOW/INDEX/OFFSET | When building complex analytical patterns |
references/field-parameters.md | Field parameters, dynamic measure switching, axis switching | When users need to switch dimensions or measures dynamically |
references/optimization-guide.md | Query plans, VertiPaq, FE/SE architecture, CALCULATE optimization, iterators, composite models, Direct Lake, debugging workflow | When optimizing slow measures or debugging |
references/anti-patterns.md | 19 common mistakes, performance killers, incorrect patterns, dynamic format strings | Review before finalizing any measure |
references/visual-calculations.md | Visual calculations: RUNNINGSUM, MOVINGAVERAGE, PREVIOUS, NEXT, COLLAPSE, templates | When user needs visual-specific calculations (running sums, moving averages) |
references/user-defined-functions.md | UDF syntax, reusable parameterized DAX logic, TMDL expressions [Preview] | When user needs reusable function definitions or asks about UDFs |
Core Principles
- Research First — Search Microsoft Learn MCP for latest patterns before writing DAX.
- Understand Evaluation Context — Read
references/evaluation-contexts.md.
- Measures Over Columns — Calculated columns consume memory, can't be context-aware.
- Variables for Readability —
VAR/RETURN evaluated once, constant once assigned.
- Push to Storage Engine — Avoid row-by-row formula engine iteration.
- Test Everything — Validate with
dax_query_operations.
- Document Intent — Every measure needs a description.
Evaluation Contexts
Every DAX expression executes in a filter context + zero or more row contexts.
Misunderstanding contexts is the #1 source of wrong results.
→ Read references/evaluation-contexts.md before writing any non-trivial measure.
Workflow
Step 1 — Understand Requirements
Gather: metric name, business definition, aggregation type, time intelligence needs,
filter context requirements, and formatting.
Step 2 — Research Best Practices
- Search Microsoft Learn:
microsoft_docs_search / microsoft_code_sample_search
- Check existing measures:
measure_operations — list all current measures
- Check model context:
table_operations, relationship_operations, column_operations
Step 3 — Write DAX
Follow these formatting standards:
-- Standard measure template
[Measure Name] =
VAR _variableName = <expression>
VAR _anotherVariable = <expression>
RETURN
<result expression>
Naming Conventions:
| Measure Type | Prefix/Pattern | Example |
|---|
| Base aggregation | Direct name | Total Sales |
| Percentage | % prefix | % Margin |
| Year-to-Date | YTD prefix | YTD Revenue |
| Year-over-Year | YoY suffix | Revenue YoY % |
| Previous period | PP prefix or PP suffix | PP Revenue |
| Running total | RT prefix | RT Sales |
| Rank | Rank prefix | Rank Sales |
| Count | # prefix | # Customers |
| Helper (hidden) | _ prefix | _MaxDate |
Variable Naming: Prefix with _ + camelCase: _totalSales, _previousYear, _filteredRows
Step 4 — Implement with MCP
Use measure_operations to create the measure with: tableName, name, expression,
formatString, description, displayFolder.
Step 5 — Validate
Test EVERY measure using dax_query_operations:
-- Basic: does it return a value?
EVALUATE { [Total Sales] }
-- Context: aggregates correctly by dimension?
EVALUATE SUMMARIZECOLUMNS(DimProduct[Category], "Sales", [Total Sales])
-- Filter: respects filters correctly?
EVALUATE CALCULATETABLE(
SUMMARIZECOLUMNS(DimDate[Year], "Sales", [Total Sales]),
DimProduct[Category] = "Electronics"
)
Step 6 — Optimize if Needed
See references/optimization-guide.md for engine architecture, query plan analysis,
CALCULATE optimization, iterator patterns, and debugging workflow.
See references/anti-patterns.md for 18+ common mistakes with fixes and benchmarks.
Common DAX Patterns
Base Measures
-- Always qualify column references with table name
Total Sales = SUM(FactSales[SalesAmount])
Total Cost = SUM(FactSales[CostAmount])
Gross Profit = [Total Sales] - [Total Cost]
% Margin = DIVIDE([Gross Profit], [Total Sales])
# Orders = DISTINCTCOUNT(FactSales[OrderID])
# Customers = DISTINCTCOUNT(FactSales[CustomerID])
Avg Order Value = DIVIDE([Total Sales], [# Orders])
Other Patterns (in reference files)
- Time Intelligence →
references/time-intelligence-patterns.md (YTD, QTD, MTD, WTD, YoY, fiscal, semi-additive, calendar-based)
- Ranking & Window Functions →
references/advanced-patterns.md § WINDOW/INDEX/OFFSET
- Advanced →
references/advanced-patterns.md (New/Returning Customers, ABC/Pareto, TREATAS, ISINSCOPE, PATH, Top N with Others)
Calculation Groups
Modify how existing measures behave — eliminating multiple variants per measure.
See references/calculation-group-patterns.md for Time Intelligence, Currency,
Scenario Comparison, Aggregation Type templates, precedence rules, and format strings.
Field Parameters
Enable dynamic switching of measures/columns on visuals.
See references/field-parameters.md for creation, TMDL syntax, PBIR bindings,
calculation group pairing, and limitations.
Visual Calculations
DAX calculations defined directly on a visual (not in the model). Simpler for
running sums, moving averages, vs-previous comparisons. Cannot be created via
MCP tools — report-level only. See references/visual-calculations.md.
Related Skills
| Skill | When |
|---|
power-bi-semantic-model | Model schema defines available tables, columns, relationships |
power-bi-report-design | Measure catalog feeds into Design Spec visual bindings |
power-bi-performance-troubleshooting | DAX optimization, query plan analysis |
power-bi-business-analysis | Measure requirements define what to build |
Performance & Debugging
See references/optimization-guide.md for FE/SE architecture, query plans,
CALCULATE optimization, iterators, Direct Lake, and debugging workflow.
See references/anti-patterns.md for 19 common mistakes with benchmarks.
Quick rules: Separate CALCULATE filter args (no &&) • Filter dim columns not fact • DIVIDE() for safe division • No context transition on fact tables • No nested iterators on facts • VAR is constant (won't re-evaluate under CALCULATE)
Debug steps: Isolate (EVALUATE { [Measure] }) → Decompose VARs → Check context (VALUES) → Check relationships → Check data
