Relationships are important, and not just among humans. Relationships also matter when it comes to your data. Without a clear view of data relationships, you can’t gain much insight from that data.
As with people, though, data relationships can get complicated. The good news is that this is where Power BI comes in, and PBRS from ChristianSteven can help. Let’s take a closer look at how relationships are defined in Power BI.
What are Power BI Relationships?
Power BI Relationships show the connection between two or more tables. In other words, they provide a clear view of how these tables relate to each other. More specifically, model relationships connect a column from one table to a column in a different table.
In Power BI, you cannot display the data for more than one table without a relationship, so it’s important to learn how relationships work if you want a comprehensive viewpoint. These relationships automatically travel in a single direction, though bi-directional filtering is a possibility in some cases.
Once you’ve established table relationships in Power BI, you can use queries to get answers about those relationships.
How are Relationships Defined in Power BI Desktop?
The Power BI designer will detect relationship cardinality on its own. This means that once you get the hang of Power BI Desktop, you can easily see how relationships are defined, and you won’t have to put in any extra work to define those relationships yourself. Within Power BI, there are four main cardinalities:
- One to many
- Many to one
- Many to many
- One to one
Each type serves a different purpose, though some are far more common than others.
One to Many Relationships
One to many relationships are one of the two most common relationship definitions in Power BI Desktop. A one to many relationship occurs when one column in the first table relates to many columns in the second table.
For example, a one to many relationship might give you insight about a specific quarter’s sales and inventory. The sales column from one table may relate to several inventory items from the second table.
Many to One Relationships
The many to one relationship is the other one of the two most common relationship types. It’s just the opposite of the one to many relationship. In other words, the relationship occurs when several items in the first table relate to just one item in the second. The same sales and inventory example from above would apply here if you were to place the inventory table before the sales table.
It’s easy to switch back and forth when it comes to one to many and many to one relationships. Doing so can help you examine your data from multiple angles.
Many to Many Relationships
Many to many relationships are more complex than one to many or many to one relationships. In these relationships, many items from two tables relate to one another. Designers don’t often use this option, and when they do, it’s for complex sets of data. Keep in mind that you may see duplicate values in both sets of data if you use many to many relationships.
One to One Relationships
In a one to one relationship, one item from the first table relates only to one item from the second table and vice-versa.
This type of relationship is rare and not often used in business data settings. As a matter of fact, Microsoft warns that one to one models can result in inadequate data.
If you do use the one to one relationship, make sure that it’s not the only relationship in your data model. Otherwise, you risk missing out on important connections.
Working With Power BI Desktop Relationships
Once you’ve learned the different types of relationships, it’s time to start working with them so that you can get some real answers from your data.
When working with relationships in Power BI Desktop, you may start noticing the benefits right away. For one thing, relationships let you analyse the connections between multiple tables at the same time.
Relationships also give you a clear and concise view, so there’s no need to wrap your brain around complex data without a visual representation. This way, you may notice connections that you might have otherwise missed.
Finally, Power BI’s automated calculations mean that you always get accurate results.
Cross Filter Direction
Different data models come with different cross filter directions. They can run either left to right, right to left, or both. Work with the different cross filter directions to get a closer look at how your data points impact each other and see what may happen if you were to alter any of those data points.
DAX and Bi-Directional Cross Filtering
For some relationships, you may use DAX to achieve bi-directional cross filtering. Using this function has its pros and cons, and it may take a bit of practice to get the hang of using it.
While bi-directional cross filtering may work for some specific sets of data, it can also make things more ambiguous when you query that data. More often than not, single-direction cross filtering will work just fine.
That said, there are several DAX functions that you might use to customise your relationship models. Make sure that you first familiarise yourself with Power BI relationships as a whole. This way, you can avoid unnecessary complications and know exactly when these tools can help you.
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