35 Effective Power BI Best Practices in 2024

Power BI enables analysts and scientists to turn unorganized data into visually meaningful representations. To get the most out of Power BI, aspiring professionals must understand best practices. I'll walk you through each of the 20 Power BI best practices in 2023 with examples from the real world throughout this extensive document. Whether you're a college student exploring analytics or a newbie data analyst, mastering Power BI will skyrocket your career and make you a valuable asset. Power BI visualization best practices are also important when it comes to showcasing your reports to higher leadership who require only top-shelf information for quick decision-making. Power bi training is an essential toolkit that aspiring analysts should have in their array of skillsets.

What is Power BI?

Microsoft's Power BI is an important resource for businesses looking into the complexities of visualization of information and making choices. Power BI shines as the preferred choice among professionals for converting raw data into useful knowledge because of its user-friendly interface and comprehensive features. Its fluid features enable the smooth sharing of information across groups, making it an essential asset for companies focused on improving their data-driven decision-making. In summary. Power BI development best practices and power BI data flow best practices are the two important elements that belong to the Power BI best practices handbook and should be kept in mind when preparing and publishing a report.

35 Power BI Best Practices

Here are the top Best Practices for Effective Power BI usage that should be followed to make your report more efficient and streamlined. You can learn more about best practices used by top companies by enrolling in Business Intelligence online courses by reputed organizations like KnowledgeHut and other online courses.

1. Limit the number of visuals in dashboards and reports
2. Remove any additional visual interactions
3. Row-Level Security (RLS) should be enabled
4. Use Custom Visuals from Microsoft AppSource
5. Use of Hierarchical Filters Should Be Avoided
6. Sort the data for Power BI reports
7. Use the On-Premises Data Gateway
8. Use Separate Power BI Gateways for "Direct Query" and "Scheduled Refresh"
9. Test Each Custom Visual on a Report to Ensure Fast Report Load Time
10. Limit Complicated Measures and Aggregations in Data Models
11. Import Only Necessary Fields and Tables Instead of Entire Data Sets
12. Reduce the Amount of Data Loaded on the Page
13. Using version control systems(VCS) in Power BI
14. Choose Storage Mode for Tables Appropriately
15. Cross-Check Referential Integrity for Relationships
16. Ensure Reports and Data Sources Are in the Same Region
17. Use hierarchy to drill down and up the chart
18. Avoid Bi-Directional and Many-to-Many Relationships Against High Cardinality Columns
19. Avoid Using Floating Point Data Types
20. Replace the Auto-Generated Date Table with a Custom Date Table in Your Model
21. Optimize DAX Formulas
22. Use Power Query Editor for Data Transformation
23. Utilize Composite Models
24. Implement Incremental Refresh
25. Monitor Performance with Usage Metrics
26. Opt for DirectQuery Over Import Mode
27. Use Power BI Embedded for Scalability
28. Leverage Power BI Templates
29. Implement Row-Level Security (RLS) Hierarchies
30. Regularly Update Power BI Desktop and Gateway
31. Optimize Visual Interactions
32. Document and Standardize Data Models
33. Utilize Advanced Analytics Features
34. Implement Data Compression Techniques
35. Optimize Report Layout for Mobile Devices

1. Limit the number of visuals in dashboards and reports

Dashboard overload hinders comprehension by users. Emphasize the top 5 visuals from an overall of say, 20, pointing out key insights for greater impact. Striking the right balance ensures that important information is communicated effectively. As an analyst, I have experienced this in my career, where stakeholders are only interested in a limited set of metrics though there are lot of information that can be picked from the dashboard. Power BI best practices are always mandated by analytics managers.

2. Remove any additional visual interactions

Want to know the secret of improving Power BI report performance? Here’s a hint! You can make that possible by removing unnecessary interactions between visuals. Unwanted interactions mislead users and make it hard to read findings. When cross-filtering isn't adding analytical value, switch it off. This proactive strategy emphasizes user-friendly interfaces, which leads to the optimal viewing experience achievable.

3. Row-Level Security (RLS) should be enabled

Improve the privacy of data by restricting users to information that is relevant to their function. RLS is vital for protecting sensitive financial data. Implementing RLS guarantees data access remains private and secure while complying with rigorous security standards. If your report deals with sensitive content that requires only certain viewers to have access to it, then these are the power BI best practices you should adopt for great security and stability.
In my organization, I have seen the best use case of RLS where employee performance feedback was rolled out as a dashboard with only the specific employee and their manager can have access to and view the performance report. This means the organization can release all feedback in one dashboard but then employ RLS to make it secure.RLS, from a security perspective, is a very important Power BI best practices element.

4. Use Custom Visuals from Microsoft AppSource

Certified graphics provide dependability and security. Explore these images for exclusive and most used data displays. Using approved specific illustrations enhances the visual appeal and dependability of your data representations, delivering a reliable analytical experience.

5. Use of Hierarchical Filters Should Be Avoided

To boost user experience and performance. Select simple filters over hierarchical ones for a smoother analysis journey. Improving user experience through streamlined navigation improves report response and user satisfaction. 

For example, always make sure that the data requires a hierarchical filter or not, and take this decision based on the level of data and its granularity, Pan India sales vs state-wise sales.

6. Sort the data for Power BI reports

Enrich the user experience by arranging data in a way that is easy to understand. Product classification streamlines reporting and analysis for greater understanding. Data organization that is intuitive aids in data interpretation, resulting in improved efficiency and beneficial reporting processes.

Stakeholder always wants minimal inputs from their side, and the data to be sorted in a meaningful way for the best visual comparison. When I was building a campaign performance monitoring dashboard for near real-time product availability and stock for the Instamart growth team, I was asked to present data on decreasing availability and increasing sales by sorting the data. As this was a report viewed by multiple managers, it saved an overall 4-5 mins per session.

7. Use the On-Premises Data Gateway

To ensure secure access to in-house data sources. Connect with ease using the Power BI service, improving data accessibility and reliability. Deploying an on-premises data gateway ensures safe and effective access to locally stored data, hence improving the reliability of your data sources. This is also an important point in Power BI best practices for better data storage and access. I saw this firsthand when the data server was moved from Singapore to Mumbai in my organization, which led to better data management cost optimizations, and improved security.

8. Use Separate Power BI Gateways for "Direct Query" and "Scheduled Refresh"

By isolating gateways, you can boost performance and utilization of resources. This ensures that real-time queries and scheduled refreshes are dealt with promptly. Isolating gateways according to query type improves overall Power BI performance by eliminating resource overloading and delays.
This is mostly a standard practice in data platform management for startups like Zomato or Swiggy where realtime metrics are required to make important decisions. In these cases, the real-time queries and the daily or weekly reports are channeled through different warehouses with different resource optimizations and speeds, as this is very important for low latency and cost savings and also to prevent overloading issues that might affect other users.

9. Test Each Custom Visual on a Report to Ensure Fast Report Load Time

Study the impact of customized visuals on report rendering. Unoptimized images can slow down the report, greatly affecting the user experience. Custom visuals are thoroughly evaluated to ensure optimal performance, which adds to a fluid and dynamic reporting experience.
Testing visuals before publishing is a 101 on Power BI best practices needed by analysts

For testing custom visuals, 1. Insert your customized image into your report. 2. Check data consistency and its visual representation. 3. Put your interactivity and responsiveness to the test. 4. Double-check the accuracy and reliability of the data. 5. Assess performance in various settings. 6. Collect user feedback for future improvements.

10. Limit Complicated Measures and Aggregations in Data Models

To improve clarity and efficiency, simplify calculations. Reducing complexity reduces processing time, enhancing overall performance. Optimizing computations improves data model efficiency, enabling quicker and more resource-efficient processing of information.

For example, if you want to calculate the user sessions per hour or city for an quick commerce project, you can calculate the measure in the query directly, instead of creating a measure within Power BI, and increasing the warehouse overhead. Also, if you want the metric only in a city and day level, you can use a table with daily session count directly or calculate in query directly and bring the aggregated numbers to Power BI instead of raw values.

11. Import Only Necessary Fields and Tables Instead of Entire Data Sets

Improve report response by importing just the necessary data. For a more efficient user experience, avoid overloading reports with extra data. Importing only the essential data items improves report loading times, giving a more efficient and simple analysis. When it comes to best visual representation and reducing the clutter, these are the power bi best practices that you can employ in your report.

Again, a very important practice used in most data-driven and cost-sensitive firms, where only relevant data is required, as 80% of the decisions are taken by using the top 20% of information.

12. Reduce the Amount of Data Loaded on the Page

Improve performance by reducing data that isn't needed load. For effective handling of huge data sets, use pagination or dynamic loading. Implementing effective data loading methods eliminates sluggish report performance and ensures a pleasant experience for users, especially when dealing with massive datasets. This is one of the most important best practices for effective Power BI usage.

Use the edit query to apply required filters and load only the required data, this can make refresh faster and reduce load on the data platforms like Snowflake, MySQL, etc.

13. Using version control systems(VCS) in Power BI

Version control is a great way for developers to work with Power BI, to use it follow the steps.

Create a Git repository, a.gitignore file, and stage/commit changes  to use version control systems in Power BI. Connect to a remote repository to collaborate, push/pull changes, establish features/bug fixes branches, and tag releases. Enhance development and collaboration workflows by integrating version-controlled assets into Power BI Service . VCS come under power bi design best practices that improve the collaboration and tracking of changes from a dev point of view, as it provides a deeper control and history management.

14. Choose Storage Mode for Tables Appropriately

By selecting the right storage mode, you can significantly enhance query performance. For large fact tables, try using the "Import" option to improve performance.  

Power BI's Composite Data Model enables easy connection to multiple data sources. By merging imported and DirectQuery tables, this allows for large-scale data models to be prepared seamlessly. Selecting the best storage mode helps optimize data retrieval, improving query performance and overall efficacy when handling massive data sets. Storage selection is a crucial Power BI best practices element that needs to be followed with utmost importance.

In my experience with large models which I use for calculating availability of items for quick commerce, we have mutliple tables and load them as composite data sources to integrate in Power BI  through defined relationships between them. Otherwise loading a huge table with 2M+ records would crash Power BI and make it unusable.

15. Cross-Check Referential Integrity for Relationships

Establishing well-defined relationships enables accurate analysis. Referential integrity checks ensure that data is consistent and reliable. Referential integrity checks ensure the accuracy and dependability of table relationships, ensuring the integrity of your results from analysis.

For example, in an Ecom setup, a foreign key linking the "Orders" table to the "Customers" table is a possibilty. A referential integrity check guarantees that each order is associated with a real client, preventing data discrepancies.

16. Ensure Reports and Data Sources Are in the Same Region

By synchronizing reports and data sources, you can minimize delay. Hosting both in the same Azure region increases total report speed by optimizing data retrieval. Co-locating reports and data sources decreases transmission latency, making the reporting ecosystem quicker and more productive. Power BI best practices for datetime variables are often overlooked by many analysts, but as we can see they can improve the overall stability and reliability of the report.

17. Use hierarchy to drill down and up the chart

The usage of hierarchies in  Power BI enriches the user experience through the usage for drill-down and drill-up actions. In a time-based hierarchy, for example (Year > Quarter > Month), users may drill down from yearly to quarterly or monthly details to get deeper insights. Drill-up, on the other hand, allows the users to move back up the hierarchy. This hierarchical structure improves data exploration capabilities by simplifying navigation and analysis.

At Instamart/Blinkit/Zepto like companies, it is important to look at current stock levels of campaign items from a city > store level across different times of the day, for example, before 12 PM, after 4PM and 10 PM closing stock, for this having a drill down chart can work wonders as the stakeholders can quickly identify stock outs and plan accordingly.

18. Avoid Bi-Directional and Many-to-Many Relationships Against High Cardinality Columns

Use relationships effectively for better performance. Consider different possibilities for complicated situations to save too much information processing. In complex analytical settings, thorough investigation of different kinds of connections and options helps to effective processing of info and greater efficiency. Relationship management comes under the Microsoft power bi performance best practices realm where the performance of the report is checked.

A single one to one relationship is the best for indexers to work faster in backend( for example, capital city to country mapping), while bidirectional and many to many relationships( for example, countries to state names) can have a slight impact to the model depending on the cardinality of the dataset. More many to many relationships mean more query processing and hence overload at high cardinality situations.

19. Avoid Using Floating Point Data Types

Use whole numbers or decimals data types to avoid precision issues. Using the correct data types ensures reliable calculations. Using precision-appropriate data formats minimizes calculation mistakes, which produces reliable and precise analytical outputs.
Precision in computations require the data to be stored in a certain way and in SQL, for optimal computation, there are different precision point datatypes like NUMBER(38,0) , NUMBER(38,5), DECIMAL, INTEGER etc.If you are sure that the value you are seeking is only a number without a decimal point, you can alter the dataset to only use INTEGER or NUMBER(38,0) types. The more suiting the datatype is, the better is the memory utilization and hence query performance. Efficient floating point number usage is one of the easier ways that I use to employ Power BI best practices when it comes to better visual and relevant points.

20. Replace the Auto-Generated Date Table with a Custom Date Table in Your Model

A custom date table gives you greater control over date-related operations. Include additional columns for fiscal quarters and holidays to meet certain requirements for reporting. Modifying a date table to meet unique reporting needs offers more freedom and accuracy in calendar-related calculations which as an analyst you will face in most cases.

21. Optimize DAX Formulas

Improving the speed and efficiency of Power BI through optimizing DAX for better ways of computing and querying data. They should therefore lie on the optimization of some of the many operations involved in the calculations through minimizing the use of more functions, use of some optimized patterns to speed up the rendering of reports and doing others.

22. Use Power Query Editor for Data Transformation

Leverage Power Query Editor's intuitive interface to cleanse, shape, and enrich data before loading it into Power BI. Employ transformation steps like filtering, merging, and appending to ensure data quality and relevance for insightful visualizations and analysis.

23. Utilize Composite Models

Microsoft

If you need to integrate numerous datasets, it is possible to do it easily in Power BI to create a single perspective for the detailed investigation. Implement various levels and types of Hadoop data connections, along with modes of storage and aggregations, to import data from SQL databases, Excel spreadsheets, clouds, and other sources for swift processing and reporting in large-scale environments.

24. Implement Incremental Refresh

Optimize the data storage of refreshed report data by accessing only the fresh data or any new data that has been added after the last refreshing was done, to minimize the time taken in processing data. Use refresh schedules based on date intervals or other conditions, to ensure reports are updated only when necessary, while reducing the computation needed.

25. Monitor Performance with Usage Metrics 

One can track the usage metrics regularly to understand the proper utilization of Power BI dashboard. This tracking and analyzing of metrics will help to understand the performance bottleneck, resource optimization planning and allocation, and improve user experience.

26. Opt for DirectQuery Over Import Mode

DirectQuery mode is the one that would be best suited for the source system in Power BI since it enables users to establish a direct connection to the system, thereby avoiding the need to load massive amounts of data into the application for analysis. It also saves storage space and for large scale and high frequency update sources, enhancing the ability to provide up to date information to the users.

27. Use Power BI Embedded for Scalability

Growth your Power BI solution smoothly by enabling reports and dashboards inside other applications, irrespective of the use of Power BI Power BI Embedded offers flexible pricing options, allowing you to customize resources based on specific usage needs. This ensures scalability and gradual adjustment of quotas to support the chosen embedded analytics model.

28. Leverage Power BI Templates

Accelerate report development and maintain consistency across your organization by leveraging Power BI templates. These pre-built templates offer standardized layouts, designs, and data connections tailored to specific industries or use cases, reducing development time and ensuring adherence to branding and reporting standards.

29. Implement Row-Level Security (RLS) Hierarchies

Resource adequacy: Take extra measures in proactively protecting the data in use by applying row by row security (RLS) in Power BI. RLS lets you limit the vision of individual rows of data based on the roles of users or their positions in an organization or that hierarchy so that data that is to be kept private will not be viewed by other folks who have no business doing so.

30. Regularly Update Power BI Desktop and Gateway

Update your Power BI tools regularly for the most recent features, improvements or security updates on Power BI Desktop and Gateway. Such updating means the availability of new features or additional possibilities, higher operations speed, and problem solving, improving the users’ experience as well as stability and security of the systems’ work.

31. Optimize Visual Interactions

Microsoft

Enhance the quality of interaction between and usability of visuals in Power BI reports, which should help make gained insights clearer to users. Superimpose business logic to layer objects on top of each other to depict functionality, establish a narrative history between related visuals and also to operability to enhance the user's taste and analytical journey.

32. Document and Standardize Data Models

Ensure that there is clarity and coherence when dealing with data by putting a lot of effort in documenting the data models in use in Power BI! The use of clear terms allows defining data sources, relations, calculations and metadata and complements collective work in concordance with the goals of the organization.

33. Utilize Advanced Analytics Features

Marketers will be able to access deeper analyses and predictive models through advanced features in Power BI, an organizational tool. Forecasting 4, clustering, regression analysis to analyze data and discover trends, patterns and relations in data to help the user decide since armed with good data he/she can make good decisions.

34. Implement Data Compression Techniques

There are some specific types of data compression available within Power BI that the author suggests can help to achieve better storage density and more effective querying. Implement practices such as columnar storage, different types of data encoding and partitioning to reduce the footprint and make sure that it yields high retrieval rates for analysis irrespective of the volume of data.

35. Optimize Report Layout for Mobile Devices

Microsoft

Improve navigation and labeling by ensuring that the report layouts and view are optimized for Power BI desktop and mobile systems. Implement graphics and page layout that is optimizable to fit across devices, the mobile first layout should enhance user experience for individuals using smartphones and tablets when viewing reports.

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Conclusion

In conclusion, understanding the best practices of power bi reveals a route to remarkable effectiveness and simplicity in data analytics. I've discovered the art of creating impactful reports by judiciously limiting data visualizations, streamlining data models, and ensuring security through Row-Level Security (RLS). Using Microsoft AppSource-certified visualizations and region-specific hosting improves Power BI's stability and efficiency even more. These methods, when paired with sensible gateway management and thorough evaluation of exclusive visuals, not only boost the consumer's experience but also reinforce the foundation for accurate and quick decision-making. Courses like KnowledgeHut Power BI training can be your best tool when it comes to learning these as a beginner or intermediate-level professional. Employing Microsoft power bi best practices is one of the important points that help professionals toward excellence in Power BI usage and building value for clients and cost optimizations for the company.