Quick Measures in Power BI

What if I told you there's no need to write laborious DAX expressions in Power BI? Doesn't that sounds great? I personally enjoy writing the DAX expressions from scratch because it helps to get to know the data well and you can tailor your calculations. But if you don't like writing the DAX expressions from square 1 then you should consider "Quick Measures". Power BI always makes your task easy in visualizing your data and quick measures are something that helps you to create measures in few seconds.

Doesn't that sound amazing? Yeah!! As the name suggests creating measures just by dragging and dropping is an accentuating feature of quick measures. I consider it to be the future of measures in Power BI. In this blog, I will showcase step by step process to create quick measures. I will be working on the Sample Superstore data.

You can find the quick measures right next to the new measure on the top or else you can right-click any of the available table options and you can easily find new quick measures. After selecting the quick measure you will land upon a toggle that will highlight all the measures available for your current dataset.

To start off we will focus on time intelligence functions. If you consider Tableau this is just to drag and drop but in Power BI if you do not use quick measures then you need to write the measure every time. Time intelligence functions help you to get the best out of your date function. Functions such as YTD, MTD, QTD are called time intelligence functions. To create it with the quick measure we will select the YTD in calculation and select the sum of sales and order date from fields respectively.

After that click ok and you will notice that a measure is created in your field and you can expand the measure to see the calculation behind it. Similarly, you can do the same for QTD and MTD calculations.

After digging the time intelligence functions let's move to running total. Running total is sometimes called cumulative total. The process is quite similar to the time intelligence function. After selecting ruuning total in the calculations you need to drag the average of sales and order date.

Suppose you need to look for sales only from the east region. The possible solution is to apply a filter which can be done in quick measures too. You need to select the filter value in calculations and select the sum of sales and region.

There is a pool of options available which can make your life easy and this list of calculations gets update frequently and every time you will get more add-ins calculations.The use of quick measures is a boon as it saves a lot of time while creating a measure. I firmly believe that quick measures will come heftier in the future as compared to measures.

Thanks for Reading Let's connect on LinkedIn.

Comments

Copying Bookmarks from one Power BI report to another

Let's think of a scenario, where you want to copy the bookmarks from one report to another. Most obvious approach is to just do a copy paste of the bookmarks. What's wrong with this approach? This approach only works for all visuals but not for bookmarks and field parameters. If you are not familiar with basics of bookmarks and field parameters do refer to the beginners guide for bookmarks and introduction to field parameters . Then how do you copy the bookmarks? Power BI enhanced report format (PBIR) for Power BI Project files (PBIP) will help you in achieving this. Let's check it out, I have 2 reports one contains the bookmark called Bookmarks PBIR Test (origin) and other one is Rolling Average PBIR Test (destination) . Before we get started, you have to enable Power BI Project save option under preview features. Once enabled, restart Power BI desktop. There is a TMDL icon appearing on the left pane. What is TMDL and what's in it for me? There's a lot of possi...

Playing with Totals in Power BI

Are you a fan of matrix visual in Power BI? If you are as I am, I always struggle to get the correct totals and get something else instead of the totals it can be average. After a lot of research and going over different community posts, finally we have found 3 common scenarios that can elevate your matrix to the next level. To start with, I am using Sample Superstore data. Let's first explain the 3 different scenarios that we will tackle - We would like to show both Total Sales and Average Monthly Sales across different categories and different periods. We would like to show the Average Sales in the row subtotals and Total Sales in the column subtotals. Last and the most interesting scenario is to show the Total sales excluding the furniture sales in the row subtotals and total sales in the column subtotals. Let's start by getting the correct totals in a matrix. Generally, if use basic Sum, Average... functions in your measures then most likely...

Identify and Delete Unused Columns & Measures

Heavy dashboards and a bad data model is a nightmare for every BI Developer. Heavy dashboards can be slow due to multiple reasons. It is always advised to stick with best practices. Are you still figuring out about those best practices then you should definitely have a quick read on Best Practice Analyser ( link ). One of the most common issues with slow dashboards is unused columns and unused measures. It is very normal to load some extra columns and create some test measures in your dashboard but as a part of cleanup process those unused columns and unused measures should be removed. Why we are removing them? Because if you keep them then ultimately it will increase the size of your data model which is not a good practice. How to identify the culprits (unused columns and unused measures)? In today's blog we will provide you with 2 most common external tools which will help you in identifying the culprits. More external tools😒. Who's going to pay for this? To your surprise...

Analyst in Action

Search This Blog