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.
2022-04-04 (first published: 2017-11-29)
4,697 reads
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.
2022-04-04 (first published: 2016-09-21)
5,124 reads
In this article I want to provide an introduction to the vital set of functions that help you to use a time element when analyzing data
2017-10-27 (first published: 2016-06-06)
5,788 reads
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.
2022-04-04 (first published: 2016-03-17)
4,869 reads
As a part of his "Function / Iterator Pairs" mini-series, Business Intelligence architect, Analysis Services Maestro, SQL Server MVP, and author Bill Pearson introduces the DAX MAX() and MAXX() functions, discussing similarities and differences. He then provides some hands-on exposure to the use of each, particularly in combination with other DAX functions, in generating "largest numeric values" to meet differing needs within our PowerPivot model designs.
2022-04-04 (first published: 2015-01-14)
6,549 reads
