Power BI is one of the great, powerful, and intelligent business tools that can transform raw data into actionable insights. Well even if you have large datasets and complex models, performance still matters. Well if you are looking to ensure optimal performance, then it is necessary to optimize your Power BI data models.
Here in this article, we have discussed the best practices that can help improve Power BI performance. So if you are interested in this field, you can enroll in the Power BI Training in Noida. Because Noida is a great place to learn such skill-based courses. So let’s understand these practices in detail:
Power BI Practices:
Here we have discussed the best Power BI practices, that can help you understand it in detail. Well, if you are employed in a company that resides in Bangalore, you can take your Power BI Training in Bangalore. After successful completion of the training, you can apply for the higher position in aunty company situated in Bangalore.
1. Limit the Number of Visuals:
When you use too many visuals in a single report it can slow down your report performance. This is why because each of the visuals may need data processing and rendering. You can limit the number of visuals by eight per report page and grid to one per page. For the tiles. Keep a limit of 10 per dashboard. Doing so can help in reducing the amount of data that needs to be fetched and displayed.
2. Use On-Premises Data Gateway:
Well, it would be wise to use the on-premises data gateway instead of personal mode. The personal mode imports data into the Power BI which can cause resource limitations. If we use standard mode, ten data may stay in its original location only. So if you use a gateway this may minimize data duplication, reduce memory usage, and avoid potential performance problems.
3. Use Separate Gateways:
A live connection in the Power BI service (Direct Query) continuously connects with data sources in real time. Data refresh is scheduled to update imported data at specific times. Utilizing the identical gateway for live connections and scheduled data refreshes may overwhelm the system during refresh periods, resulting in slower live connections.
Ensuring the gateways are separate allows both functions to operate efficiently without interference.
4. Use Calculated Measures:
If you use complex models and aggregations in data models can slow down query performance. Also if you use calculated measures that are computed during query implementation, they are more efficient than calculated columns. Well if you apply filters it can also aid in this process.
5. Calculations to the Source:
It is advisable to push calculations to the source as this will shift the processing to the data source, improving query processing efficiency. Having greater proximity to the origin may boost the speed of performance.
6. Prefer the Star schema over the Snowflake Schema
The star schema is less complex and more normalized in structure than the snowflake schema. The snowflake schema necessitates more intricate queries because of its multiple interconnected tables.
The star schema helps to speed up query processing and simplifies maintenance by reducing the number of joins needed. Enhancing query efficiency, minimizing data duplication, and streamlining report creation.
7. Slicers
Slicers are a great way that allow users to navigate the data, but they affect the performance cost. Well, each of the slicers generates two queries:
● One fetches the data and the other fetches the selection details
● If you add too many slicers, it can slow down the performance.
● You can use the filter pane to remove unwanted slicers.
8. Host Reports in the Same Region:
A Power BI tenant is the specific space where an organization’s data, reports, and dashboards are stored. Microsoft runs data centers globally to offer and manage its services. Every data center is located in a particular area.
Keeping both tenant and data source in the same region helps to reduce network latency. This allows for faster transfer of data, execution of queries, and ultimately quicker retrieval of data and rendering of reports.
9. Divide the Data:
Dividing is the technique in which the large data is divided into smaller parts called divisions based on specific criteria. A columnar index is a type of index that stores and organizes data by columns rather than rows. In this method, only necessary fields and tables are imported which improves data loading efficiency and reduces resource consumption.
Conclusion:
From the above discussion, it can be said that it is worth investing in Power BI Course. Well, you can find the Best Institute for Power BI in Delhi, that provides training for the same. Doing so will add a credential to your portfolio and make your resume stronger. So if you are looking to improve your Power BI skills and learn advanced optimization techniques, consider enrolling in the course.
