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Exploring Advanced Relationship Properties In Power BI Copilot

I’ve been playing around with Power BI Copilot a lot recently, and following on from my recent posts on tuning Copilot by editing the Linguistic Schema and setting the Row Label and Key Column properties in this post I want to delve into some of the advanced properties of relationships. I won’t pretend to understand everything that’s going on here – I’m still learning all this – but I thought it would be useful to share what I’ve found out so far.

These properties are described in this YouTube video from the Q&A Modeling Bootcamp series that I referred to in my Linguistic Schema post. They available to set in Power BI Desktop on the Relationships pane of the Q&A Setup dialog by clicking on the “Add to relationship” dropdown box” when creating a new relationship:

For my testing I created a semantic model containing a single table called Journeys. Each row in this table represents a leg of a journey; the journeys are identified by the values in the Journey column, each leg is identified by the values in the Stop column. When a person starts a journey there is a row with Stop = 1 and Stop Type = Start; they may then call in on one or more towns, indicated by Stop Type = Call; and when the journey ends there is a row with Stop Type = End. The Mode column contains the mode of transport, the date represents the date of the leg of the journey, and there is a Booked column which tells you when the journey was booked.

For example, in this data Chris started a car journey in London on January 1st, called in on Oxford, then finished his journey in Birmingham on January 2nd.

There’s also a measure called Journey Count which does a distinct count on the journey column:

Journey Count = DISTINCTCOUNT(Journey[Journey])

Now Copilot does a pretty good job with this table without any tuning. For example, the prompt

Whose journeys started in London?

is correctly interpreted most of the time as “Show the person for journeys where Town is London and the Stop is 1”:

This is a great example of where the LLM adds extra smarts that aren’t present in the old Q&A feature. But some similar questions don’t get answered so well. For example:

Whose journeys ended in Glasgow?

…gives this result:

Not only is the number shown irrelevant the answer is wrong, because Helen also ended a journey in Glasgow. So some tuning is needed.

Here’s where I’m going to show what I did and how it fixed the problem but I want to make it clear that there may be better ways of doing this. I’m sure this time next year I’ll look back at this post and cringe and my ignorance but hey, we all have to start somewhere!

I added several relationships to the model, for example this Verb relationship to indicate that People end Journeys in Towns on Dates where Stop Type is “End”.

In this case the People column indicates the subject, the verb is “end” and the objects is the Journeys table. There is a prepositional phrase “in” to indicate that journeys end in towns. Journeys end on the date given in the Date column. The fact that a journey has ended is indicated by a condition that the Stop Type column contains the value “End”. The prepositional phrase, Time and Condition were added with the “Add to relationship” dropdown.

After this I got the following, correct response to the prompt

Whose journeys ended in Glasgow?

Here’s another example. Consider the prompt:

Who passed through Birmingham?

The original model gives the following, reasonable response:

But let’s say that when we write “passed through” we only mean Stop Type = Call, so journeys like the one Chris made that start or end in Birmingham don’t count.

With the following relationship:

…you not only get the correct result:

…you can ask questions like:

Who passed through Birmingham and on which dates?

As you can see, the “Add to relationship” dropdown box adds even more ways to configure relationships and even more ways to tune Copilot. Knowing your English grammar and parts of speech is going to help a lot here – and this is something that may not come easily to someone working in tech. I like this kind of challenge though. Who knows, maybe the ability to set up a Linguistic Schema will be as important as the ability to write DAX for Power BI developers soon?