Implementing Function-playing Dimension in SSAS Tabular Fashions

To start with I’d like to clarify what a Function-playing dimension really means. Then I’ll categorical the way in which you possibly can implement it in a SSAS tabular mannequin.

Once you hyperlink a dimension to a reality desk a number of occasions for logically distinctive roles you’re utilizing a role-playing dimension.

The important thing factors are:

1.       You’re linking a reality desk to a dimension a number of occasions. The relationships are outlined by linking a number of international keys within the reality desk to a single key within the dimension desk.

2.       Every linkage represents a single position or idea

The preferred role-playing dimensions are DimDate and DimTime. Do you wish to see the right way to implement Function Enjoying Dimensions in Energy BI, Click on right here and right here.

NOTE: The pattern is from Microsoft “AdventureWorksDW” for SQL Server 2012 and may be completely different from your individual information warehouse design.

As an illustration, in a gross sales system that you’ve got one thing like FactInternetSales reality desk which has a number of hyperlinks, or relationships, to a DimDate or DimAddress for distinct ideas like “Order Date”, “Ship Date” and “Due Date”.

As you see, all the above columns clearly characterize completely different meanings of date. Within the information warehouse design you’ll see one thing like this:

role-playing dimension 01

Though that is completely OK within the relational database layer, however, this kind of relationship is NOT permitted within the tabular mannequin, so what ought to we do?

Let’s take a look on the tabular mannequin in SQL Server Knowledge Instruments (SSDT) and see the way it appears after we import the mannequin straight from SQL Server information supply.

·         Open SSDT and create a brand new evaluation providers tabular undertaking (I assumed you know the way to create a brand new undertaking in SSDT)

·         Click on on “Import From Knowledge Supply”, then choose “Microsoft SQL Server” then click on “Subsequent”

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·         Enter the server title and choose “AdventureWorksDW” from the database checklist then click on “Subsequent”

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·         Entre impersonation data and click on “Subsequent”

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·         Click on “Subsequent”

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·         Right here you possibly can choose all tables and views you could import into your tabular mannequin. In our pattern we simply want “FactInternetSales” and “DimDate” tables. So tick the “FactInternetSales” and “DimDate” tables after which click on “End”.

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·         Shut the “Desk Import Wizard”

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·         Change to “Diagram View”. As you possibly can see there is only one Lively relationship between DimDate and FactInternetSales tables and each different relationships are Inactive meaning you can’t instantly use the imported DimDate for all three purposes you could cowl the “Order Date”, “Ship Date” and “Due Date”. Which means that you can’t slice and cube a single measure with all roles on the identical time, which in our instance they’re “Order Date”, “Ship Date” and “Due Date”. I clarify extra later on this submit.

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1.       Importing DimDate into your tabular mannequin a number of occasions:

In our pattern we have to import it 3 times to cowl “Order Date”, Ship Date” and “Due Date”.

a.       Delete the inactive relationships

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b.      Double click on on the DimDate desk title to rename it to a consumer pleasant title. Title it “Order Date”.

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c.       To make our pattern extra untestable I created a brand new hierarchy named “Order Date Particulars” which incorporates “CalendarYear”, “EnglishMonthName” and “FullDateAlternateKey”. A additionally renamed the columns to make the extra consumer pleasant to “12 months”, “Month” and “Full Date”. As well as, I set all different columns within the DimDate desk to “Disguise from Consumer Instruments”. I additionally renamed the “FactInternetSales” desk to “Web Gross sales”.

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d.      We now have efficiently setup the “Order Date” date and now we have to import the DimDate desk once more to help the “Ship Date”. To take action, from the “Mannequin” menu choose “Present Connections…”

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e.      Click on “Open”

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f.        Click on “Subsequent”

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g.       Choose DimDate from the checklist once more and click on “End”. This course of will import the DimDate desk to the mannequin once more. We’ll then set it as much as cowl “Ship Date”. To take action, hyperlink “ShipDateKey” from “Web Gross sales” desk to “DateKey” from “DimDate” desk.

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h.      Now repeat the above sections from b to g however, title the “DimDate” desk “Ship Date”. Repeat the above sections once more so as to add “Due Date” to the mannequin.

i.         We’re accomplished and we will merely slice and cube primarily based on all the above dates.

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j.        Because the tabular mannequin doesn’t detect the measures routinely we have to outline not less than a measure to have the ability to check the answer. To take action swap to “Grid View” and choose the “Web Gross sales” then outline a measure for “Whole Gross sales Quantity”. To take action simply click on on measures part beneath the “SalesAmount” column then click on the Sigma (clip_image021) button from the toolbar. Then rename the created measure to “Whole Gross sales Quantity”.

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okay.       Now we will check the answer by choosing “Analyze in Excel” from “Mannequin” menu

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l.         Tick “Whole Gross sales Quantity” and “Due Date Particulars” hierarchy. You’ll be able to drilldown to month and day ranges.

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m.    You are able to do the identical for every of the opposite dates or you can also make a mixture of dates if you happen to want such a report.

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2.       Creating a number of SQL Server views within the  database:

In our instance, in “AdventureWorksDW” database, we create three views for every position (Order Date, Ship Date, Due Date). We create these views on prime of the prevailing DimDate with completely different names resembling the three completely different roles. Then we import these views into our tabular mannequin and hyperlink every of them to the “Web Gross sales” desk utilizing the suitable international key. As the entire course of is identical as what we’ve accomplished beforehand within the first resolution, I’m not going to clarify it once more. So, on the finish of the day, we may have one thing like this within the database:

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Now you can import the above views to your tabular as an alternative of importing the entire DimDate desk a number of occasions. This can scale back the database measurement and it’s a bit simpler to grasp. Nevertheless this resolution is similar to the primary resolution . Principally the structure is sort of the identical, however, the way in which we handle the tables is a bit completely different.

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And the identical leads to Excel:

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3.    Creating a number of measures: 

The third resolution, which might be the perfect for almost all of use instances, is totally the alternative of what we now have accomplished to this point. Properly, I can say that the structure is sort of completely different. On this resolution we DO NOT take away the Inactive Relationships and furthermore, we DO NOT import a number of copies of Date dimension.

Role Playing Dimension in SSAS Tabular

What we must always do on this case is to create new measures for every position which suggests we may have the next three measures in our instance:

1- Whole Gross sales Quantity by Order Date

2- Whole Gross sales Quantity by Ship Date

3- Whole Gross sales Quantity by Due Date

What we’re doing on this resolution is that we handle to make use of the connection which is related to the roles. To try this we simply must implement the info mannequin to activate the connection we’d like. We will simply energetic and inactive relationship in DAX utilizing USERELATIONSHIP operate. The USERELATIONSHIP operate, disables all energetic relationships first, then prompts a desired relationship. USERELATIONSHIP operate can be utilized as part of different capabilities that take filters as arguments. Which means that we all the time use USERELATIONSHIP as part of a CALCULATE operate (or different capabilities that settle for filter arguments). Due to this fact, the above three measures will seem like under:

1- Whole Gross sales Quantity by Order Date:= SUM(‘Web Gross sales'[Sales Amount])

2- Whole Gross sales Quantity by Ship Date :=  CALCULATE(SUM(‘Web Gross sales'[Sales Amount]), USERELATIONSHIP(‘Date'[DateKey], ‘Web Gross sales'[ShipDateKey])

3- Whole Gross sales Quantity by Due Date :=  CALCULATE(SUM(‘Web Gross sales'[Sales Amount]), USERELATIONSHIP(‘Date'[DateKey], ‘Web Gross sales'[DueDateKey]))

As you possibly can see within the first measure we haven’t used USERELATIONSHIP. The explanation is that the measure makes use of the connection which is energetic by default within the mannequin, subsequently we don’t must implement it once more. The opposite two measures then again are implementing related relationships for use throughout the measures.

Managing Role Playing Dimensions in SSAS Tabular with Measures

Lastly, right here is the way it appears like if you analyse the mannequin in Excel:

Managing Role Playing Dimensions in SSAS Tabular with Measures in Excel

Every of the three options mentioned above have professionals and cons.

Professionals of the primary two options, importing a number of Date dimensions:

1- In case your mannequin is a small mannequin then it could be faster to develop the mannequin

2- It could be simpler for the top consumer to have completely different Date choices. You’ll have separate slicers within the visualisation layer for every position.

3- You’ll be able to have only one measure and slice and cube it by completely different roles individually


1- In case your mannequin shouldn’t be small and you’ve got way more position taking part in dimensions to handle then you definitely’ll find yourself importing these dimensions a number of occasions which isn’t environment friendly

2- Having numerous completely different position taking part in dimensions everywhere in the mannequin will likely be actually complicated for the top consumer and you’ll really want to spend extra time/cash to coach the top customers

3- You devour extra storage and reminiscence which is once more not that environment friendly 

Professionals of the final resolution, creating a number of measures:

1- You need to use all of the roles side-by-side as you actually have a separate measure for every position

2– You aren’t importing a number of copies of the roles, as an illustration, you might have only one Date dimension that can be utilized to slice and cube your entire measures throughout the entire mannequin

3- It’s extra environment friendly when it comes to storage and reminiscence consumption

4- Your mannequin is way more tidy if you don’t have a number of roles everywhere in the mannequin


1- In giant fashions with numerous completely different roles, creating numerous completely different measures to help completely different roles could be time consuming and in addition a bit arduous to keep up

2- The measure names are getting lengthy

3- Having numerous completely different measures that look very comparable is usually a bit complicated for the top consumer 

All accomplished!

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