Tips and Tricks for Optimising Performance in Power Query

With the help of the flexible tool Power Query, users can extract, clean, and transform data with amazing efficiency. Learning Power Query Excel as part of your Excel Training will greatly improve your data management skills. However, guaranteeing optimal performance becomes crucial as datasets get bigger and more complicated. This blog will explore how to improve Power Query’s speed so that your data processing is always quick, easy, and effective. 

Power Query in Excel: A Game-Changing Tool 

Microsoft Excel’s Power Query function allows users to connect to numerous data sources, perform data transformation operations, and then load the modified data into the spreadsheet. It offers a user-friendly interface for processing data, making it a valuable tool for experts who manipulate and analyse data.  

Why Performance Optimisation Matters  

The speed of Power Query becomes increasingly important as you work with bigger information and more intricate operations. Frustration, delays, and lower productivity can result from slow or inefficient data processing. By enhancing Power Query’s speed, you can keep your data processes efficient and responsive so you can concentrate on getting insights from your data rather than waiting for it to process. 

Tips and Tricks for Optimising Power Query Performance 

Let’s examine a few strategies for improving the efficiency of power query:

  1. Reduce the amount of data you’re working with wherever you can. Early in the transformation process, filtering and deleting pointless columns can greatly speed up succeeding phases.  
  2. Utilising query folding, which sends some operations back to the data source for processing, is a benefit of Power Query. When possible, use native query folding to use the data source’s processing capabilities.  
  3. Power Query incurs processing costs for every transformation step. Integrating related changes and eliminating repetitive activities, try to reduce the number of stages.   
  4. Turn off the automated date/time recognition tool in Power Query settings if your data is free of date or time information. This can save the process from wasting time on unneeded conversions. 
  5. Select the “Load to” option that best meets your requirements. For smaller datasets, loading data to a table in your worksheet is appropriate; for bigger datasets, loading data to the data model (Power Pivot) is more effective.  
  6. Remove the unnecessary columns and rows from your data for your research. Performance is enhanced, and Power Query must process less data.  
  7. When doing sorting and filtering tasks, adding index columns can enhance performance. Power Query can more effectively optimise these processes thanks to index columns.  
  8. Grouping activities may need a lot of resources. When working with huge datasets, use them sparingly and prevent over-grouping. 
  9. Choose the data types that are best for your columns. Data processing can be slowed down by using incorrect or unused data types.  
  10. If your worksheet has several data sources, update what is required to reduce the total refresh time. 

Enhancing Power Query Performance with Advanced Techniques  

Power Query’s base programming language is M. You can find bottlenecks and places that require improvement by profiling your M code. Tools like Power Query’s “Performance Profiler” may give users insight into which processes use the most time and resources.  

Although Power Query’s custom functions can be useful, extensive custom functions might cause performance issues. To make your searches efficient, utilise pre-built functions and common transformations whenever feasible. 


You can access a vast array of data transformation options with Excel’s Power Query, but performance optimisation becomes crucial as your data processes get more complex. By putting the tips in this blog into action, you can ensure that your Power Query processes continue to be efficient and responsive. Your time will be freed up, allowing you to focus on extracting insights from your data rather than waiting for transformations to complete. Learning how to optimise Power Query performance as you grow in your Excel training will offer you the efficiency and confidence to handle challenging data.

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