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# Why Your Power BI Report is So Slow - And How to Speed It Up?

Power BI is one of the most popular tools used to analyze and visualize data. It is widely used in offices across India, especially in fast-growing cities like Delhi and Chennai. These cities have many companies working with large amounts of data, making report speed very important.

In Delhi, the focus has shifted from just learning Power BI to using it well in real business situations. People are now comparing [Power BI Course Fees in Delhi](https://www.cromacampus.com/courses/best-power-bi-training-in-delhi-ncr/) based on whether the course covers speed and performance topics.

Let’s explore the real technical reasons why Power BI reports get slow - and how you can fix them quickly.

## Your Data Model Might Be Too Heavy
Power BI works better when your data is arranged in a star schema - this means one main table with smaller lookup tables connected to it. If everything is in one big table, Power BI needs more memory to work. This slows things down. Also, avoid columns with too many unique values like IDs, invoice numbers, or timestamps. These are called “high-cardinality” columns. They take more space and make filters slower.

Remove columns that you’re not using in visuals. Every column takes up memory, even if it’s not shown. In Chennai, where many tech startups create data dashboards for clients, this mistake is common. Students in a [Power BI Course in Chennai](https://www.cromacampus.com/courses/power-bi-course-in-chennai/) often learn the hard way that a bad model leads to poor performance.

## DAX Measures Can Hurt Speed

Many users make the mistake of using complex DAX when simple formulas would work. For example, using SUMX(FILTER(...) when a simple SUM(...) would be enough. This uses more memory and takes longer to calculate.

Nested measures also cause delays. If one measure depends on another, Power BI has to calculate multiple things at once. This stacks up when the data is large.

A common fix is using variables in DAX. Variables help Power BI calculate things just once and reuse the result. This saves time.

Advanced [Microsoft Power BI Certification](https://www.cromacampus.com/courses/microsoft-power-bi-certification/) classes teach how to write cleaner, faster DAX. They also explain how to reduce the load on the Formula Engine, which runs your calculations.

## Too Many Visuals Can Slow Things Down

Every visual on your report page sends a separate query to the engine. So if you have 10 visuals, that’s 10 queries at once.

Many users add charts, slicers, and cards all on the same page. It looks good, but it kills performance.

Use fewer visuals on each page. Group related information together. Hide extra visuals behind bookmarks or navigation buttons.

Avoid using too many slicers. Try using one dropdown slicer or filter pane instead of many slicers for the same data.

In Chennai, one company found that just reducing visuals on a page cut load time by 40%. That tip became part of their internal Power BI Course in Chennai training.

Also, avoid heavy visuals like maps or decomposition trees unless needed. These take longer to load and use more resources.

## Your Refresh Setup Could Be the Problem
Many reports are slow not when you open them - but when they try to refresh with new data
.
If you’re refreshing the full dataset every time, it takes longer. Instead, use incremental refresh. This tells Power BI to only refresh new or updated data.

Also, avoid using Excel files stored on your desktop. These are hard for Power BI Service to access. They can break your refresh. Use data from cloud sources like SQL Server, SharePoint, or OneDrive.

Some Power BI users write complex steps in Power Query that don’t fold. Query folding means Power BI pushes the work to the data source, instead of doing it itself. No folding means slower refresh.

If you're preparing for Microsoft Power BI Certification, mastering query folding and refresh setup is a must. It’s often the key to building reports that scale with large datasets.

## Use Summary Data, Not Every Detail

Do you really need every row of data in your report? Often, the answer is no.

Use summarized or aggregated data. For example, show monthly totals instead of daily transactions. You can prepare summaries in Excel or SQL before loading into Power BI.

Summarized data is lighter. It loads faster and makes calculations quicker.

In New Delhi, many large companies deal with high-volume transactional data. This approach helps them build faster reports for leadership teams who only want top-level views.

## Table: Quick Fixes for Slow Reports


| Problem | Quick Fix Suggestion| 
| -------- | -------- | 
| Flat data model    | Use star schema with dimension tables   | 
High-cardinality columns   | Remove or avoid in filters  | 
Complex DAX with iterators | Use variables and rewrite for simplicity | 
Too many visuals per page  | Limit visuals; use bookmarks or drill through  |
Refreshing full dataset daily  | Enable incremental refresh  | 
Excel from desktop as source | Use cloud storage or SQL Server | 
Auto Date/Time turned on | Turn off; use custom date table| 


## Sum up,
Build a simple, clean data model using a star schema. Avoid too many unique values in any one column. Write efficient DAX using variables and fewer nested measures. Keep pages simple - too many visuals slow down your report. Use incremental refresh to save time. Don’t load more data than you need - summarize before importing. Turn off Auto Date/Time to reduce memory usage. Prefer cloud or database sources over local Excel files.
