10 Common Power BI Mistakes and How to Avoid Them

Power BI is widely used across organisations to create interactive dashboards, automate reporting, and visualise insights in real time. But just like any powerful tool, it can lead to more confusion than clarity if not implemented correctly.

Here are 10 common Power BI mistakes and how you can avoid them to build dashboards that are fast, useful, and genuinely drive decision-making.

1. Overloading Reports With Too Much Information

It's easy to get carried away with visuals in Power BI. You’ve got bar charts, pie charts, maps, KPI tiles - and they’re all just a drag-and-drop away.

But reports overloaded with too much information often confuse rather than clarify.

How to avoid it: Think of each report page as a narrative. Ask yourself: what decision is this report meant to support? Limit visuals to what helps answer that question. Use drill-throughs, filters, and navigation to guide users through additional layers of detail, rather than displaying everything upfront.

2. Using the Wrong Visuals for the Data

Choosing a fancy chart type might look impressive, but if it confuses your audience, the message gets lost. Other times, certain visuals may not suit the data it ingests, such as line charts used for categorical data, pie charts with too many slices, and gauges that leave viewers scratching their heads.

How to avoid it: Match visual types to the nature of your data and your audience. For example, use:

• Bar/column charts for comparisons

• Line charts for trends over time

• Cards/KPIs for highlighting single values

• Scatter plots for relationships

The goal isn’t to impress - it’s to inform, or better still, illuminate.

3. Neglecting Data Modelling Best Practices

A messy data model leads to broken relationships, incorrect totals, and slow reports. Many users build visuals off flattened tables from Excel or CSV files, which don’t always scale well.

How to avoid it: Use a star schema design wherever possible - fact tables for transactions, and dimension tables for categories like dates, customers, or products. Define one-to-many relationships clearly, and keep your model clean and logical. Avoid circular references and ambiguous joins.

4. Not Naming Measures, Tables, and Columns Clearly

If your report contains fields named Column1, MeasureX, or Table2, it’s a red flag because it can confuse users and make maintenance harder.

How to avoid it: Name your fields clearly and consistently. Use spacing and capitalisation that aligns with how your business talks about data. For example, use “Total Sales ($)” instead of “totalsales_1”. It helps both your users and your future self make sense of the report months later.

5. Overusing Calculated Columns Instead of Measures

This is a classic performance trap. Many users come from Excel and default to calculated columns - even when measures would be more efficient.

How to avoid it: Use DAX measures to calculate values dynamically. Calculated columns are stored in memory and add to dataset size. Measures only calculate when needed and tend to perform better, especially on large datasets.

6. Ignoring Performance Optimisation

Slow-loading reports are a common complaint. They waste time and reduce adoption, especially in larger organisations.

How to avoid it:

• Limit the number of visuals per page

• Use Power BI’s Performance Analyzer to identify slow queries

• Avoid complex DAX calculations in visuals

• Reduce dataset size by removing unused columns or applying filters at the source

You can also consider aggregated tables or incremental refresh for large datasets.

7. Not Controlling User Access Properly

Failing to implement access controls means everyone sees the same data - which might not always be appropriate. This can lead to privacy issues, especially in sectors like healthcare, finance, or HR.

How to avoid it: Use Row-Level Security (RLS) to restrict access to data based on user roles. For example, a state manager in NSW should only see data for their region, not national figures. In Power BI Service, assign roles and test access before publishing to wider teams.

Check out our data story on Row-Level-Security to explore how to securely manage data access in Power BI: Power BI Row-Level Security: How to Control Data Access Effectively

8. Skipping Documentation and Version Control

Without documentation or version history, teams struggle to troubleshoot or improve reports. One misplaced filter or updated calculation can introduce hidden errors.

How to avoid it:

• Document key measures, filters, and logic within Power BI using DAX comments

• Keep a versioning log in your project folder

• Store PBIX files in SharePoint, OneDrive, or version-controlled repositories like Azure DevOps or GitHub for larger teams

Even a basic naming convention helps maintain consistency and transparency.

9. Failing to Plan for Mobile and Tablet Users

Many teams forget to check how their dashboards look on smaller screens - only to find key visuals cut off or unreadable when accessed from phones or tablets.

How to avoid it: Use the Mobile Layout view in Power BI Desktop to build optimised versions of your reports for mobile users. Focus on showing the most critical KPIs at the top and ensuring touch-friendly navigation.

This is especially relevant for field sales teams, warehouse managers, or executives checking updates on the go.

10. Not Leveraging Power BI Service Features

Too often, teams stop at building the report and don’t make use of Power BI Service’s cloud capabilities. As a result, they miss out on automation, sharing, and version control.

How to avoid it:

• Set up scheduled refreshes so reports always show the latest data

• Use data-driven alerts to notify users when KPIs hit thresholds

• Share via Power BI Apps for curated experiences across teams

• Explore deployment pipelines for staging content between test and production environments

These features take your reporting from static to strategic.

Power BI is more than just a reporting tool - it’s a business intelligence platform. But like any platform, the value you get depends on how well it's set up and maintained.

Avoiding these 10 mistakes will help you build faster, cleaner, and more impactful dashboards - ones that users trust and leadership actually use.

If your business is facing challenges with Power BI performance, usability, or adoption, our Sydney-based data consultancy can help. From quick audits to end-to-end reporting solutions, we partner with organisations to turn underperforming dashboards into real business assets.

Contact us for a free consultation - we’ll help you pinpoint what’s holding back your reports and how to fix it.