Learning DAX is easy once you install the PowerPivot for Excel 2010 add-in and get practical exposure to using functions, operators and values in DAX formulas. Bill Pearson, business intelligence architect and author, kicks off another Stairway series designed to get you using DAX and PowerPivot quickly to provide actionable business intelligence in your own environment.
As a part of his “Function / Iterator Pairs” mini-series, Business Intelligence architect, Analysis Services Maestro, and author Bill Pearson introduces the DAX Product()and ProductX() functions, discussing the syntax, uses and operation of each. He then provides hands-on exposure to Product()and ProductX(), respectively, in returning the product of numbers in a column and in returning the product of an expression evaluated for each row in a table.
Continuing his examination of the evolving DAX “Function / Iterator Pairs,” Business Intelligence Architect, Analysis Services Maestro, Microsoft Data Platform MVP and author Bill Pearson introduces the DAX Concatenate() and ConcatenateX() functions, discussing the syntax, uses and operation of each. He then provides hands-on exposure to Concatenate() and ConcatenateX(), in joining two text strings into a single text string, and in returning the concatenation of an expression evaluated for each row in a table, respectively.
Business Intelligence Architect, Analysis Services Maestro, eight-year Microsoft Data Platform MVP and author Bill Pearson introduces the DAX CountA() and CountAX() functions, discussing the syntax, uses and operation of each. He then provides hands-on exposure to CountA() and CountAX(), in counting non-empty cells in a column, and in counting nonblank results when evaluating the result of an expression over a table, respectively.
Business Intelligence Architect, Analysis Services Maestro, eight-year Microsoft Data Platform MVP and author Bill Pearson introduces the DAX All() function, discussing its syntax, basic uses and operation. He then provides hands-on exposure to All(), focusing largely upon its most basic uses in manipulating filter context.
Business Intelligence Architect, Analysis Services Maestro, eight-year Microsoft Data Platform MVP and author Bill Pearson introduces the DAX CALCULATE() function, discussing its syntax, basic uses and operation. He then provides hands-on exposure to CALCULATE(), focusing largely upon its most basic uses in evaluating an expression in a context that is modified by specified filters.
Business Intelligence Architect, Analysis Services Maestro, and author Bill Pearson introduces the DAX ALLSELECTED() function, discussing its syntax, uses and operation. He then provides hands-on exposure to ALLSELECTED(), focusing largely upon its most popular use in supporting “visual totals” in Power BI.
Business Intelligence Architect, Analysis Services Maestro, and author Bill Pearson introduces the DAX ALLEXCEPT() function, discussing its syntax, uses and operation. He then provides hands-on exposure to ALLEXCEPT(), focusing largely upon its most popular use in removing filters from all columns in a table - except the filters we specify.
Business Intelligence Architect, Analysis Services Maestro, and author Bill Pearson introduces the DAX DATEADD() function, discussing its syntax, uses and operation. He then provides hands-on exposure to DATEADD(), focusing largely upon a popular use in creating prior-period values at multiple Date hierarchy levels.
Business Intelligence Architect, Analysis Services Maestro, and author Bill Pearson introduces five DAX Time Intelligence functions related to Dates: DATESBETWEEN(), DATESINPERIOD(), DATESMTD(), DATESQTD(), and DATESYTD(). He discusses the syntax, uses and operation of each, and then provides hands-on exposure to the functions in Power BI.
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I have this data in a table called dbo.NFLTeams
TeamID TeamName City YearEstablished ------ -------- ---- --------------- 1 Cowboys Dallas 1960 2 Eagles Philadelphia 1933 3 Packers Green Bay 1919 4 Chiefs Kansas City 1960 5 49ers San Francisco 1946 6 Broncos Denver 1960 7 Seahawks Seattle 1976 8 Patriots New England 1960If I run this code, how many rows are returned?
SELECT TOP 2
json_objectagg('Team' : TeamName)
FROM dbo.NFLTeams;
See possible answers