Top 5 Power BI DAX tricks for super effective Power BI dashboards [Webinar]

In the previous webinars, many of you have asked us, "Oh, how did you do that trick? How do you do the year-to-date slicer? Can you change the measures dynamically in charts?"

And yes, all of these and much more can be solved using DAX in your Power BI. Tricks like these actually enhance the usability and the user-friendliness of your dashboards in a really massive way. Andrej Lapajne will share his best methods, which you'll be able to apply in your own Power BI reports.

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  1. Looking around in Power BI
  2. Starting from scratch
  3. Looking at the relationships between tables
  4. Setting up calendar dimension
  6. How can Zebra BI visuals help you?
  7. Looking at variances
  8. Combining multiple visuals
  9. Creating a YTD switch
  10. Creating a KPI switch
  11. Putting it all together

As a fantastic product as Power BI is, it still tends to have a few problems.
First of all, sometimes dashboards simply are not effective enough, no matter how colorful they are. Secondly, they tend to get really complicated when building. People are using bookmarks, hiding charts and putting lots of elements on the page, which is really difficult to build and even more complicated to maintain.

We will show you Power BI DAX modeling best practices, which will speed up the development of your dashboard pages and reports, and make them much easier to manage in the future. Thus, we will focus especially on how to use DAX in a smart way to enhance your dashboards. Together, we'll prepare a nice dashboard that you'll be able to share with end-users and your management. You can find more examples of Power BI reports here.

Looking around Power BI

Start with the basics. First of all, you should begin with getting your time series and calendar right. These contain your months, quarters, years, days, weekdays, etc. The core element of every Power BI model is a good calendar dimension.

Once you have that, you can gradually start to build things like Actual vs. previous-year comparison. In the example below, you can look at this year's sales revenue and growth compared to the previous year's.

You can do a monthly comparison versus the previous year, which is a very basic concept but you need to know your DAX to do this in Power BI.

The next thing is the switch. It's a very simple way to switch from monthly to year-to-date results, so you can actually change the view and see the accumulated values.

Power BI Dashboard Example: Sales Monthly and YTD

Here we are working with just one visual. Everything else is just done with Power BI DAX, so you can switch between different views. You can also use the same technique to switch the shown KPI. For example, if you want to change the view from the revenue and see the whole page for the gross profit, you just need to click on the gross profit and everything will change to show the gross profit. You can build multiple pages that just take advantage of this model. Using the same model, it's easy to build different views, monthly views, trends, structured tables and comparisons.

We'll add the comparison to the plan, by using the three most important techniques: previous year (PY), actual (AC) and plan (PL), with which you can build nice variance analysis reports, like the one below that is completely dynamic. In this way, you can just dive into the details.

You can also change the order of elements. Besides having the previous year, actual and plan, you can also put the variance in between. Just shuffle things around and reorder them, even change the view from year-to-date to monthly, until you've built yourself a nice variance report you are satisfied with.

Starting from scratch

Let's start with a completely blank Power BI document. The first step, of course, is just to get some data. In this example, we have imported the data from an existing excel spreadsheet, specifically the sales demo database which includes data like date, product IDs, customers, salespersons, business units, and so on. It also includes three major KPIs or measures: the revenue, the costs and gross profit, and an additional field that's in a column called "scenario".

Scenario column indicates whether this is actual data or planned data and it's all joined together in the same table. We call this a fact table. Then we also have typical dimensions and business units, such as divisions, groups, etc. There are also lots of customers from different regions and countries.

After we load everything into Power BI, we can start analyzing, trying to build a model and make sense out of all information, in order to gain some insights.

Looking at the relationships between tables

Switch to the last tab showing the relationships between tables. This is the so-called star schema model is the best way to model things in Power BI. When you load data into Power BI, you should always try to plan for a star schema, which means that you have one big fact table with all the data and measures. Then you can build all your dimensions around it.

Power BI has already created some relationships, which you can explore further, by going back to the report tab.

Back in the report view on the right side, under Fields, you can select, for example, the Revenue and the Date fields. Now we are actually starting to do some sort of analysis with native Power BI visuals. Below can see the trends based on the yearly values and you can even drill down into it. You can see that there's sort of a yearly trend and that revenue is growing over time, but it's really hard to see what is going on. The labels are not very intuitive and clear.

But this is really not an analysis. What we need, first of all, is to add a comparison. Once you compare one value with another value you start to understand what is going on: is this better or worse than planned? How much better, how much worse? Is it better than the growth from the previous year?

Once you have the comparison in your model, then you can actually start analyzing things and then communicating them. We can start by working on the date values.

Setting up the calendar dimension

Every good model in Power BI starts with the calendar dimension. To add it to the report we'll switch to the data view. Just click New table on the top to create a new table. We'll call it Calendar and choose the CALENDAR function, which actually builds a list of dates.

Below is an example of a calendar from the first of January to 2016 to the end of 2018. This will show us a simple column called Date.

Calendar = CALENDAR("2016-01-01, "2018-12-31")

And yes, that's exactly what we already have in our sales table. The difference is that now we have one row per day and we can now add new columns. If you click on the New column button in the top bar, you can add new columns using time functions. The first one we'll do is just called "Year", and we'll just extract the year from the date we already provided. That's really simple to do.

The function YEAR will extract this and simply return the year. The only thing left is to format the year by using the FORMAT function. To get the year you just type the year and four Y letters. This formula returned the year, like before, but this time it's considered as a text.

"Year", FORMAT([Date], "yyyy"),

Now you can add another column to showcase months. Let's call it "Month"and we'll use the FORMAT formula again: Format the date, this time using three M characters.

"Month", FORMAT([Date],"MMM"),

This is how you can build your custom columns which you will use in your reports. You can add the quarter, as well. Use the format date to extract the data and use Q for "quarter". This returns a number between one and four. But, if you want to have values like Q1, Q2, Q3 and Q4, you can do that as well, by adding the letter Q in front of the number and use concatenating.

"Quarter", Q & FORMAT([Date],"Q"),

That's the standard way in Power BI. But there's an even easier way, as shown below. In this case, the backslash displays the letter Q, which is followed by the number of the quarter.

"Quarter", FORMAT([Date],"\QQ"),

There are other functions, like weekday, weeknum for week number, and so on, that you can use to build other columns in your date or calendar table.


However, there's another way how to do this, and that's with the function called ADDCOLUMNS, which automatically searches for the dates in your database and automatically finds the minimum-maximum date and builds everything automatically. Even better, you can use the ADDCOLUMNS function in combination with CALENDARAUTO function.

You can simply copy and paste the whole formula from bellow. This formula has built the whole calendar table with all the columns and you can tweak individual properties, like should the year be shown as a four or two-digit number.

    "Year", FORMAT([Date], "yyyy"), 
    "MonthNo", MONTH([Date]), 
    "Month", FORMAT([Date],"MMM"),
    "Quarter", FORMAT([Date],"\QQ"),
    "YearMonth", FORMAT([Date],"YYYY-MM"), 
    "WeekdayNo", WEEKDAY([Date],2), //1-Sun..Sat, 2-Mon..Sat
    "Weekday", FORMAT([Date],"ddd"), 
    "WeekNo", WEEKNUM([Date], 2),
    "Week", "W" & WEEKNUM([Date], 2) )

There is also an option to build your calendar dimension in Power Query, which is another part of Power BI.

You can now use the created calendar dimension instead of date field from your sales table, allowing you to be much more flexible. For example, you can now say: "I want to see my sales by year."

The last thing to do is to link the new dimension to your data, which you can do by going back to the model view. Click on the Date field within the Calendar table and just link it with the Date field in the Sales table, using drag-and-drop. You should now hide the Date field in the Sales table by right-clicking because we will not use it in the report anymore. Instead, we'll just use the date from the calendar table.

If the order of years is showing in the descending order, you can switch to your field that you want to sort by, and select Sort Ascending to sort the years correctly. When you add the month names to the chart and you sort ascending, you don't get the right sort order, because it will be sorted alphabetically. So you need to tell Power BI how to sort the months. These are things that look completely obvious to every Excel user but these are real, real challenges that people are facing when they start using Power BI.

You can solve this straight from your report view by selecting the month name, go to Column tools and select Sort by column button. You will find your month number, which is also one column in your calendar dimension.

Switching to Zebra BI for Power BI

We can now we can start analyzing data and start building dashboards. To do this, we recommend you first import Zebra BI visuals from the Microsoft AppSource.

Let’s analyze the revenue by month, and use the year as a slicer. This allows the end-user to choose the year, which is a basic requirement for many reports. Drag the Year measure onto the canvas and switch to the Slicer visualization and set it as a dropdown.

But this is still not enough, because all we can do now is to change the year and see the monthly development. The only thing that you can really do here is to see if the results are better in the summer or in winter and trends and outliers. What's more important, is to compare our actual revenue with the planned revenue. We can do this because there are actually two types of values in the sales database. There are plan values and actual values.

So, first of all,  we need to separate actual results from the plan by building a new measure.

Let’s create a measure called "Revenue AC filtered" which shows the actual revenues. You can do this by first running a SUM function on all the values of the revenue column. To filter it by actuals you can use the CALCULATE function. The formula will first take the sum of the revenue column and with the added FILTER function, you can actually filter the sales table. Type in Sales and use the Scenario column to filter rows with AC.

Here is the end formula:

Revenue AC filtered = CALCULATE(SUM(Sales[Revenue]), FILTER(Sales, Sales[Scenario]="AC"))

We can now use this measure in the chart. For this example, we are looking at the actual sales in December of 2017. But we can easily do more. We can start by comparing this year to the previous one.

Remember the calendar dimension that we created earlier? You can now actually add another measure to calculate the value for the previous year. Just take the actual revenue and shift the year by one to look at the past year. You can do this by using the CALCULATE formula again:

Revenue PY = CALCULATE([Revenue AC], DATEADD('Calendar'[Date], -1 , YEAR))

This takes the actual revenue, which we just calculated before. Now we will use the DATEADD function, which is, in a way, most versatile and safest to work with. There are other formulas you can try, like PREVIOUSYEAR, which, while easy to use, has some caveats. You can also use the SAMEPERIODLASTYEAR, the PARALLELPERIOD and a few others.

Now you have the basic model in Power BI to start building your comparisons and you can add this revenue from the previous year into the visual. Now the magic starts to happen. Only now can we actually start building meaningful reports in Power BI.

Looking at variances

The visual has changed completely because now our visual understands that you are working with two values. You have actual values and the previous year. Our visual calculates the sum of the previous year on the left side and the actuals on the right. The visual already calculated the growth and now everything else happens automatically. You have the growth from the previous year expressed in percentages and if you click it, you will have it in absolute values, or you can click again to display both. You now have year over year values for each variance for each month.

You can just simply switch between different types of charts by clicking on the arrow on the side of the chart and just do a simple line comparison. Or you can use area charts and column charts with different types of layouts. If you have very limited space, you can just use a column chart with the variances.

If you have a very small chart and other things around it, the user can simply open a chart in the Focus mode where everything is big and the relative variances are calculated.

Check out our webinar on MASTERING VARIANCE REPORTS IN POWER BI, here.

Combining multiple visuals

Now we can start building dashboards by combining multiple visuals. We'll use the group of business units and do the comparison of actual versus the previous year. In a single chart, you have the actual, the deviation to the previous year in absolute numbers and in percent. You can do very interesting analyses already with the two visuals. For example, you can sort and see the worst performing business units and then click on it to see the details per month.

As you may have seen, we have very different business units here: baby care, wearables, audio hardware, etc. Since this is a company that deals with different types of businesses, it would help to add another hierarchy level. Add the Division field into the Category to understand this business better.

And so we have a split electronics and personal care, two completely different businesses. You can now click on an item to see the result for electronics, the wearables and mobile products, etc. An even better decision is to not just have one chart on the right but to present all the business unit groups there. You can do this by adding the business units to the Group field of the chart.

The single chart turned into small multiples and you can see all business units at once. The waterfall chart will look much, much better if you clean it up with proper labels and units. For example, you can show values in thousands. It's much better to just use the K, M, and B suffixes, which the Zebra BI visuals always put in as default. When you change the display units to thousands, you can show the K in the title instead of for each value. Simply pick the option title in the Show units in the field on the right. Now we have revenue and revenue versus previous year comparison shown in K. You can also reduce the number of decimal places or, in some cases, reduce the label density, to make things cleaner.

Some charts also need a little bit more space. You can control this by setting the category width by setting a fixed category width. This allows you to determine the exact width of your columns. Now you can analyze data to just see all the business units or just look closely at what's going on within electronics.

If you have data visualization challenges (like big and small charts side-by-side), you can use the "auto" layout in small multiples. The automatic layout will try to see if there are some large values and will try to arrange other charts around it for a better placement. You can also set the so-called largest-first algorithm, which will take care of really big charts. This usually provides better results if you have large differences between data categories.

Creating the YTD switch

This chart is already starting to make sense but we need even more flexibility. The next thing would be to create the year-to-date switch. But first let’s add a slicer for the month. The user can now select the desired month. Of course, the slicer will filter all visuals on the page, so when you switch to, for example, September, the table part of the dashboard is okay but the trends are broken. To fix this select the slicer, select Format settings in the top bar, and select the Edit Interactions button.

Now turn off the interaction for the visual with the monthly trend. You want this slicer to control everything but the time series, so when a month is selected, it's not affecting the time series. This is the simplest way to control which visuals are affected by a slicer.
You can do many more interesting things with slicers.

Now we need the switch. The switch is used so you can look at data for August or August year-to-date.

We can do it in the model view, where we'll add another table for the monthly versus year-to-date switch. This is called a disconnected table, because it's not having any relationships with other tables. We'll add the table by clicking Enter data at the top bar and we'll just add another table which we can call Period Calculation.

In the first column, we will be inserting the period calculation, and the second one will be a number and we'll just call it CalcID. We'll put monthly in the first column. This is option number one. Option number two is YTD. We created this little table that you can see bellow and it should be placed somewhere near your calendar.

When you go back to your model you have the period calculation column in the Fields. Let’s add the Period Calculation to the dashboard. You now have monthly and year to date options. Change this visual to a slicer and change the orientation to horizontal.

Now we have a button to switch between monthly or year-to-date values. At this point nothing is happening when we click the buttons, because they are not related to other visuals, so you need another Power BI DAX trick. Create a new measure and call it Selected calculation which will simply return the CalcID of the currently selected button. You can do this by using the MIN DAX function. You can see the full measure code below:

SelectedCalc = MIN('Period Calculation'[CalcID])

Just drop this into your report and display it as a Card visual. When you now use the buttons, the number in the card visual will change. But, how will we link this to the model? First, go back to my Revenue AC measure, which, at the moment simply returns the filtered column from sales. We will rename the measure and call it  Revenue AC filtered. Now add a new measure that will take into account the selected calculation and if the value is 2, calculate the year to date value.
Check out more about making and using buttons here.

This will be the true Revenue AC measure. Just add the function name switch within DAXIn the end, it should look like the function below:

Revenue AC = SWITCH ([SelectedCalc],
    1, [Revenue AC filtered],
    2, CALCULATE([Revenue AC filtered], DATESYTD('Calendar'[Date])))

We evaluate the selected button and then go to a new line by pressing SHIFT + ENTER. When the value is one, the formula simply returns my previous measure, which is now called Revenue AC Filtered.

In the second case, when you need the year-to-date value, so you can use CALCULATE to tern  Revenue AC Filtered into a YTD value by adding the DATESYTD function. Within the DATESYTD function, you need to add the date column from the calendar table. The Revenue AC measure now evaluates the selected calculation from the switch and calculates year-to-date, if necessary.

Right now the previous year measure still refers to the old measure, so make sure that it will be calculated from the new one and it'll work for both, monthly and for year-to-date. Remove the old measure from the visual and add Revenue AC instead, which takes into account the monthly, the year to date, and will work across the whole dashboard.

All of this is happening in the same visual and everything else is done with switches and dropdown menus.

Creating a KPI switch

In the trick number five, we'll use the same idea with the switch, but this time we will use it to switch between KPIs.

We want to change the charts from revenue to gross profit. Right now, we show revenue actuals and the previous year. Of course, wee can also do this for the plan. First, we will copy what we did for actuals and simply filter by the plan instead. Click New measure and use the below formula.

Revenue PL filtered = CALCULATE(SUM(Sales[Revenue]), FILTER(Sales, Sales[Scenario]="PL"))

Now we also need the dynamic measure for the plan, which, we will base on the formula for actuals. Create a new measure and paste in the below formula:

Revenue PL = SWITCH([SelectedCalc];
    1; [Revenue PL filtered];
    2; CALCULATE([Revenue PL filtered]; DATESYTD('Calendar'[Date])))

This measure will return the normal plan in the first option and, in the second option, it'll return the year-to-date values of my plan. Now we have the actual, the plan and the year-to-date. However, all of this is just for the revenue. Imagine if you wanted to do this again for the gross profit, one option is to do all of that again for the gross profit, a different KPI.

You could just copy and paste all measures and adjust them to the other KPI, but if you have three, five or ten measures, that quickly stacks up. Moreover, when you want to use those measures in your report, you need to create another visual, so you need one visual for the revenue, the second one for the profit, and so on. But we can do something else. We will use a switch and just reuse the same measure.

First, we need to add another disconnected table. Go back to the model view and click Enter data and repeat the whole procedure from before. This time, however,  we will call this the KPIs table. My first column is the KPI, and the second one will be the numbers (one, two, three) or KPIID. The revenue is KPI number one. Then there's the cost, which is number two, and the third one is the gross profit.

Load this into your model and you get another disconnected table. You can use this KPI now as another switch by changing it to a slicer visual. You can also make it into a dropdown. Then, create a measure that just returns the selection, calling it, for example,  SelectedKPI. Again, use the MIN function, which will return the KPI ID.

SelectedKPI = MIN(KPIs[KPIID])

With this selected KPI you can now switch between revenue, gross profit and costs. If you would like to change the order, since everything is sorted alphabetically in Power BI by default, you select the KPI table and set that KPI needs to be sorted by column KPIID.

Finally, you can create another SWITCH measure called Selected value to return the measure that you want.

The below formula will calculate the sum of the revenue as the first option. The second option will return the cost. Number three is the last one and will return a gross profit. This switch simply returns a different column based on the selection in the slicer.

Selected value = SWITCH([SelectedKPI];
    1; SUM(Sales[Revenue]);
    2; SUM(Sales[Cost]);
    3; SUM(Sales[Gross Profit]))

This is now the Selected value measure. Now, we have to now go back to the filtered AC revenue measure and instead of returning the actual for the revenue, we will return the actual for the Selected value, our new measure. Now, this is not revenue anymore but the actual data filtered using the selected column.

AC filtered = CALCULATE([Selected value], FILTER(Sales, Sales[Scenario]="AC"))

This is AC filtered, and now you just go to the revenue AC and rename it into an AC. This is now your generic actual measure that takes into account the year-to-date and the selection of the KPI.

Putting it all together

And now this is a completely dynamic dashboard. Now you can create pages in minutes.

Now you can put the slicers in whatever order you prefer, like KPI slicer first, then the month, then the year, and then period calculation. You can also turn off the slicer header of the slicers on the right and keep it completely minimal in order to use the space for something more important.

You can also copy the page and use the same thing for different types of measures. For example, you can add the plan, build the tables and compare previous years and actual plans by including variances that you can just reshuffle around. You can do this on one single page with only one visual.

You can add details like the business units, add more levels, create a multi-level hierarchy, etc. You can even do crazy things like removing the slicer. Because what happens if you remove the slicer? Everything still works. That's the magic of the MIN function, because even if the slicer is not there, the minimum is still evaluated, and it will return the option number one.

What you can also do is, remove the business units and use your KPIs under Group. Put KPIs into the Group data field and you'll get small multiples of the measures. Now you have your revenue and gross profit scaled in a small multiple. This helps you understand the relation of gross profit to revenue. You can also go further and create two-dimensional multiples or even multi-dimensional multiples (what a phrase). Just group by another field, which creates the two-dimensional small multiples.

You can switch from monthly to year-to-date, compare the revenue and gross profit and much more. This way It is very easy to build dashboard pages and you can even create 10 dashboard pages in about an hour. To further perfect your dashboards, you can check out what are worst dashboard mistakes in Power BI and how to avoid them.

And so, these are our top five Power BI DAX tricks. We hope we have demonstrated that it's not complete rocket science to navigate in Power BI and it doesn't take a lot to create beautiful and smart dashboards. If you want, you can take a free trial of both, Zebra BI visuals and Power BI, and try all these tips for yourself. If you need help, just shoot us an email at [email protected] and we will help you. Also, share your own creations with us and, if you like. Please follow us on our social media. Just help us spread the word about this, and keep your eyes out for our next webinars, and videos, and other big things we are doing.

We hope you've learned something new and that you have enjoyed this article. Bellow you can apply to receive the full recording of the webinar and the PBIX file with which you can create dashboards with the same data we've used in the above examples. You can work side-by-side with Andrej to make sure what you are doing is correct.

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