Working with users who like a lot of Table visuals in their reports, there is sometimes a tendency to not want to include the measure in the table visual which can result in the following annoying situation
Using another really basic example
the Fact is about Events and the join is between EventtypeKey and DateKey
Our Visual contains the Event Description from the Event Dimension. this visual could contain data items from multiple dimensions but the thing to understand here is that these dimensions are not part of the column chart visual
The Column visual contains Month name from the Date Dimension and the Number of events metric
Number of events = DISTINCTCOUNT('Fact'[EventKey])
If we click on a column the hope is that the table visual interacts and we only see Events in that month.
Not the case. You can click on a bar and you still see every event description. In this instance our join is not helping. How you you resolve this?
Adding the measure into the table visual
The connection is now there because of the measure so this works. But the user doesn’t want the measure in the table visual.
So what Next
Add a Filter to the table visual
If we ensure that we only show items where that specific measure is not blank we can finally see the visuals interact.
A simple filter and a bit of thought over the data model and the joins has resolved the issue and now we can have tables with data from other dimensions that aren’t used in the visuals
Its always nice to work through the updates by relating them to something you are working on.
Lets have a look at the Gradient Legends
lets start with a simple events chart for 2020
the Measure is
Number of Events = DISTINCTCOUNT('Event Metrics'[Event Id])
So Now lets colour the columns based on number of Events from Last year
LY Events = CALCULATE([Number of Events],SAMEPERIODLASTYEAR('Date'[Date]))
This is great because we now get an idea of how different last year was, But without any legend information its quite difficult to understand the new information
Lets add a legend
Here is where the 2020 updates come into play. we can now see that the colour is related to Last year events and it goes from 0.9K up to 1.2 K so we can see that in 2019 July had the highest number of Events.
(I have set the colour to red because in the context of our report, More events isnt actually a good thing)
Just remember, you cant add a legend data item into your visual if you are going to do this, but this is a really great new feature
We are looking at a Star Schema with a Date table connected to the Fact table by Order date Key
for these examples, the active relationship is the only one that matters
Lets have a look at all the issues arising from using the Date table without marking at a Date table
Date Slicer seems to remove the report filter flag for the last 3 years
Rolling 3 year flag= IF(DATEDIFF('Date'[Date].[Date],TODAY(),YEAR)<=3 && DATEDIFF('Date'[Date].[Date],TODAY(),YEAR)>=0,1,0)
This flag has been added to the entire report and set to 1 to make sure there is only information from these 3 years
If I add date as a table I get 2017 2018 2019 and 2020 as expected for a rolling flag.
However As soon as I change that table into a Slicer, all the years appear in the data set.
In this case from 2016. The filter stops being applied on the slicer
DAX FUNCTION SAMEPERIODLASTYEAR and the date hierarchy
We have some DAX to create SAMEPERIODLASTYEAR.
This is the DAX
LY Total = CALCULATE([Total],SAMEPERIODLASTYEAR('Date'[Date].[Date]))
Note the .[Date] at the end. Because we are using the date hierarchy to create the measure you can choose which level of the hierarchy to use. In this case we are saying we want the date level.
This will come back later
This is used in a visual and we have added Month Year which is a column in the date table.
As you can see, last year displays exactly the same as the current measure. This does not work
it works using the DateTime Hierarchy in the visual? However in this instance this date time hierarchy isn’t required. We don’t want the user to have to drill down to month from year every time.
In this example, the only field you can use for any measure that is date time specific is the date field
Mark as Date time
Always make sure you have a date table connected to a fact table
Note that the Date is now not connected to a back end hierarchy table.
Marking as Date table means that all your data within this table can be used for Date Measures
However lets look at the DAX that was created
All the Lat year measures are now erroring. this is because of the .[Date] at the end of the DAX
The date does not contain a hierarchy any more so if you have used .[Date] This needs removing. Its specifically related to the hierarchy.
A Year to day hierarchy has been created in the date table. This means that you have created a more compact data model and saved space.
And you can now use Month Year on the Axis
Date Table is Marked. How to work with it
This is part of the star schema in Power BI
Now the date table is marked as date, the Date hierarchy table is removed for Date within the Date table. this saves space and you can simply create your own date hierarchy to work with
The Active Join is on Received Date
All my measures so far are based on received date
Each Date in the fact table creates an extra date table to produce the hierarchy. So to save space, you should create inactive joins to the other dates and then remove the dates in the Fact table leaving just the keys. the model should then reduce in size
This works great for the measures. I can create measures based on the none active ones and simply choose to USERELATIONSHIP
LY Totals by Closed Date = CALCULATE([Total],USERELATIONSHIP('Complaint Metrics'[Closed Date Key],'Date'[Date Key]),SAMEPERIODLASTYEAR('Date'[Date]))
The above is an example of using the Closed Date None active join for Last years Totals
So i can have measures for Received this Year, Received Last year and Closed this year , Closed Last year (For Example)
This is all absolutely spot on. However there is more logic we need to think about. What about when the users want to create a drill through
This visual was created on the active relatioship so its recieved date
However your users may want to drill through to the following
how to do this?
Currently you may have the Active join on received date and Inactive on Start and Closed date
In my example, I have also kept the dates in the fact table along with the Date Keys for each Date.
Because they are in the fact table they all have date hierarchies.
Remove the Date Hierarchies across your entire dataset
You could keep them there and simply remove their hierarchies
File > Options and Settings > Options
You can turn off time intelligence for the specific report OR globally. the recommendation is to actually do this globally when you use a date table
This way you can use the dates in the fact table for drill down without creating unnecessary data with the date hierarchies
Role Play dimensions
If you want to drill down to all your dates on a regular basis, AND if there isn’t one main date and other dates that are not used as often.
In Power Query Editor go to your date table and create a reference table for each date
In this case the Date table has been referenced once and is named date created. date as been renamed to date Engagement
with this set up, there is only one join to each date key so no inactive relationships.
Any DAX you create can reference the correct date tables and your Dates can be removed from the fact table
the big downside is you have a much more complex schema with many more dimensions so only go for this if your dates are all frequently used.
In the example above, the user just wants to drill through and see all the dates so they can be left in the fact table in a Date Folder without their hierarchies
But this has been a really useful bit of research on marking the date table, Date Hierarchies and role playing