Power BI is a robust tool that offers an array of reporting possibilities. It helps enterprises streamline their data modeling and visualizations. However, the sheer complexity of the tool can be quite overwhelming, and the platform is only as good as its users.
Enhancing The Report Development Experience
If you are looking to improve report development and performance, here are some practical tips and advanced features that, although we all may be familiar with, aren’t always top of mind.
Simplify Data Formatting:
Advanced report development is a complex process in Power BI. Depending on your use case, here are some quick tips that can elevate your data extraction, modelling, and presentaxtion:
DAX Formatting: If your Data Analysis Expressions (DAX) are long and complex, you need to format your DAX. You can use DAX formatting to organize numbers and dates in your visuals by using a DAX formatter tool, making it easier to read.
Structuring Data Models: Speaking of formatting DAX, let’s talk about the right structure, particularly indentations and spaces. Understand the difference between a fact table and a dimension table and consolidate your Power Query steps. By ensuring you are correctly splitting, structuring, and formatting your data, your reports will be much easier to understand and read.
Segmentation and Cohort Analysis: This sounds basic, but I must emphasize their effectiveness to investigate the link between data sets. You can break down data sets into a meaningful cluster and then compare them to find any connections. You can also speed up the process with Power BI’s clustering, grouping, and binning capabilities.
Custom Date Formatting: No more formatting dates manually to your required format in modelling view. You can customize the date format in the modelling view by selecting the column containing the date and then selecting “Modeling” from the ribbon menu. From there, select “Format” and choose your desired date format.
Setting desired date format.
Integration with R: Did you know you can leverage the advanced statistical capabilities of R within your Power BI program? You can perform complex data transformation, data purification and data shaping by running R scripts in the Power Query editor.
Elevate Data Visualization:
When choosing visualizations, consider what would be most helpful for the end user. There are many different types of visualizations you can build and modify within Power BI, starting with KPI cards to adding matrix.
Measures On Rows in Matrix: Did you know you can add measures to rows in a matrix visualization? This can be done by dragging a measure from the Fields pane to the Rows area. This can be useful when you want to display multiple measures side by side in a matrix. Adding measures to rows in a matrix visualization.
Matrix Pivot Table Visualization: By default, your matrix will show you the table in a stepped layout. You can change the way the rows are displayed by going to the Formatting Tab and under the Row Headers section you can turn off the Stepped Layout option. This gives you added flexibility to display your data, as well as layer data.
Measures and Columns Organization: It’s a simple trick to organize them into folders, but not implemented often enough. Go to the “Model Tab” of Power BI Desktop, select the column/metric you want, and on the “Properties” tab just write down the name of the folder! This segregating makes them much easier to find and manage. Organizing measures and columns into folders.
Comparison Calculation DAX Functions: OFFSET, WINDOW, and INDEX allow you to perform Excel-like SQL calculations directly on Power BI visualizations with time intelligence. OFFSET retrieves results using relative positioning, while INDEX does so with absolute positioning. Meanwhile, WINDOW returns a slice of results using absolute or relative positioning. An example of using WINDOW to calculate the moving average.
New and note-worthy features are continuously added to Power BI to meet the evolving analytics and reporting needs of enterprises. But to get the most out of Power BI, your team must know how to use it.
What I Wish I Knew as a Beginner
Power BI offers so many exciting features to help you save time and gain new data insights. However, for anyone just getting started with Power BI, here’s some advice I wish I had:
Understand the Business Problem: Take a collaborative approach with your team to understand their data, perspectives, and problem. Once you learn about the business, it becomes easier for you to visualize the data in a business user-friendly way that conveys the KPIs and takeaways without overcomplicating them.
Familiarize Yourself with the Numbers: Do not focus too much on the visuals or design of your reports at first. Instead, focus on the numbers and logic, and think about the data sources you are using. Start learning tools like SQL to make the entire data modelling process simpler and unlock Power BI’s full potential.
Invest in Power BI training: By learning the ins and outs of Power BI, you can set yourself and your team up for success when it comes to data visualization. Features like ETL and data modeling tools make the program more robust, but they also have a sharper learning curve. Publishing Power BI reports and deploying them to your end users gets even more complex.
As complex as Power BI is, it is an equally fun and intriguing platform for business users. Do you have any growing pains you’ve experienced while working with Power BI? Share your favorite hidden tips and tricks of Power BI with me in the comments below.