Tools like Power BI have changed reporting allowing power users to leverage tabular cubes to present information quicker and without the (perceived) need for developers. However, experience tells us many users still want data in tables with a myriad of formatting and display rules. Power BI is not quite there yet in terms of providing all this functionality in the same way that SSRS is. For me, SSRS’s great value and, at the same time its curse, is the sheer amount of customisation a developer can do. I have found that almost anything a business user demands in terms of formatting and display is possible.

But you have invested your time and money in a tabular SSAS model which plays nicely with Power BI but your users want SSRS reports so how to get to your data – using DAX, of course. Using EVALUATE, SUMMARIZECOLUMNS and SELECTCOLUMNS you can return data from a tabular model in a tabular format ready to be read as a dataset in SSRS.

If you had the following data in your tabular model:

  ProductName   ProductCategory   Country   Sales
  Surly Steamroller   Complete bike   France   £46,575
  Genesis Day One   Frame   France   £47,987
  Genesis Day One   Frame   France   £47,987
  Genesis Vapour 20   Complete bike   France   £24,867
  Genesis Vapour 20   Complete bike   United Kingdom   £21,856
  Genesis Day One   Complete bike   United Kingdom   £47,875
  Surly Steamroller   Complete bike   United Kingdom   £27,969
  Surly Steamroller   Complete bike   United States   £46,575
  Genesis Day One   Frame   United States   £47,987
  Genesis Day One   Complete bike   United States   £47,987

 

A pattern for returning data for SSRS could be:

DEFINE
    VAR FilterCountry = @country
EVALUATE
SELECTCOLUMNS (
    SUMMARIZECOLUMNS (
        'Product'[ProductName],
        'ProductCategory'[ProductCategory],
        'Geography'[Country],
        FILTER (
            VALUES ( 'Geography'[Country] ),
            (
                OR (
                    ( FilterCountry = "All" ),
                    PATHCONTAINS ( FilterCountry, 'Geography'[Country] )
                )
            )
        ),
        "Sales", [Sales]
    ),
    "Product Name", [ProductName],
    "Product Category", [ProductCategory],
    "Sales", [Sales],
    "Estimated VAT", [Sales] * 0.2
)

To step through this…

 

  • The DEFINE part declare a variable which will take a value from a SSRS parameter
  • SUMMARIZECOLUMNS will return a CROSS JOIN of all the dimension columns entered, by passing in a measure or fact column as the last part of the block (here [Sales]) it will return only the cmbinations of dimension where there is a value for measure or fact item – particularly useful if you are dealing with date table stretching into the future.
  • FILTER will filter the SUMMARIZECOLUMNS based on the SSRS parameter value. By adding the OR and PATHCONTAINS sections you can handle multi-value parameters in SSRS. This is a good blog post explaining this approach.
  • SELECTCOLUMNS allows you to both provide friendly names for any dimensions (this is better handled in the tabular model but the amount of times it isn’t) and also perform calculations within your DAX query.

 

If your SSRS parameter was set to France and United Kingdom, the results would be:

  Product Name   Product Category   Country   Sales   Estimated VAT
  Surly Steamroller   Complete bike   France   £46,575   £931.50
  Genesis Day One   Frame   France   £47,987   £959.74
  Genesis Day One   Frame   France   £47,987   £959.74
  Genesis Vapour 20   Complete bike   France   £24,867   £497.34
  Genesis Vapour 20   Complete bike   United Kingdom   £21,856   £437.12
  Genesis Day One   Complete bike   United Kingdom   £47,875   £957.50
  Surly Steamroller   Complete bike   United Kingdom   £27,969   £559.38

 

If you set up a connection to your tabular cube in SSRS, you can paste in your DAX code, configure your parameters and you are good to go!