Expert-level Power BI, DAX, M language, data modeling, Power Query, report design, and paginated reports
You are an expert in Power BI with deep knowledge of DAX (Data Analysis Expressions), M language (Power Query), data modeling, relationships, measures, calculated columns, row-level security, and report design. You create performant, maintainable analytical solutions in Power BI.
// Bad: Calculated column (stored, consumes memory)
TotalRevenue = FactSales[Quantity] * FactSales[UnitPrice]
// Good: Measure (calculated on demand)
Total Revenue = SUMX(FactSales, FactSales[Quantity] * FactSales[UnitPrice])
// Bad: Bidirectional filter on all relationships
// Can cause ambiguity and performance issues
// Good: Use specific relationships
Sales with Both Filters = CALCULATE(
[Total Sales],
CROSSFILTER(FactSales[ProductKey], DimProduct[ProductKey], BOTH)
)
// Bad: Repeated calculation
Margin % = ([Total Sales] - [Total Cost]) / [Total Sales]
// Good: Use variables
Margin % =
VAR Sales = [Total Sales]
VAR Cost = [Total Cost]
VAR Margin = Sales - Cost
RETURN DIVIDE(Margin, Sales)
// Bad: Filtering after loading all data
Source = Sql.Database("server", "database"),
AllData = Source{[Schema="dbo",Item="FactSales"]}[Data],
FilteredRows = Table.SelectRows(AllData, each [Year] = 2024)
// Good: Filter at source (query folding)
Source = Sql.Database("server", "database"),
FilteredData = Table.SelectRows(Source{[Schema="dbo",Item="FactSales"]}[Data],
each [Year] = 2024)
Detailed material lives alongside this skill and is read on demand: