Business intelligence is essential for companies to analyze data and gain valuable insights. Two popular tools for BI are Microsoft Excel and Power BI. But how do they compare for building reports, handling large datasets, and sharing analytics?
In this comprehensive post, we'll compare Excel and Power BI across six key criteria to determine the best tool for business intelligence.
If you would like to see a full review of the two tools watch the video above.
Creating Interactive Reports
Let's start with report building. A hallmark of great BI is interactivity—allowing users to drill down and explore the data. How do Excel and Power BI stack up?
Power BI Report Building
In Power BI, interactive reports can be created with just a few clicks. Charts automatically cross-filter and update together as you build a report page.
For example, a report page might have a bar chart for sales per product category over time. With a couple more clicks, you could add line charts for revenue and profit by category.
Now all 3 visualizations are linked. If you click on a product category in the sales chart, revenue and profit will automatically filter to that category. No coding required—the interactivity is built-in.
You can also instantly add slicers to filter the entire report page by attributes like customer segment, region, date, etc. Every chart updates simultaneously, providing a seamless view into your data.
Excel Report Building
In Excel, achieving this same level of interactive reporting takes more manual work. You'd have to create separate pivot tables and charts, then use Report Connections to link them individually. It's doable but far more labor intensive upfront.
The experience is also less responsive for users. With Excel pivots, filtering one chart doesn’t automatically update all others. The interactions feel disconnected compared to Power BI's seamless cross-filtering.
For self-service business intelligence, Power BI is the clear winner for interactivity and responsive report-building. Users can easily create linked charts that filter together, allowing intuitive data exploration without any coding. Excel takes more effort to connect visualizations manually.
Performance with Large Datasets
Now let's examine performance with large datasets, an important capability for enterprise-level BI.
Power BI Performance
Power BI is engineered to deliver speed and responsiveness regardless of data size. As an example, we tested Power BI with a dataset of 5.9 million rows containing song information.
Within seconds of importing the data, we built stacked column charts summarizing views by artist and song title. Slicing the report by year took milliseconds to apply filters and update all visuals.
There was no degradation in speed compared to much smaller datasets. Even with millions of rows, Power BI allows fast data exploration and analysis.
In contrast, Excel struggles with large datasets. The maximum rows supported in a spreadsheet is 1,048,576—much less than what Power BI can handle.
But more importantly, Excel grinds to a crawl when trying to analyze millions of rows. The same song dataset corrupted Excel entirely on import. Even if it could open, basic filtering would take minutes with that much data.
However, Excel can connect to remote data and use the same technology as Power BI.
For large enterprise datasets, Power BI is undisputedly faster and more capable than handing large datasets when compared to handing the same datasets natively in Excel. Only Power BI delivers speed-of-thought interactive analytics, even with data in the millions of rows. Excel can use Power Query to achieve similar performance as Power BI but may run out of local memory for massive datasets.
Next let's examine how Excel and Power BI handle security for sensitive business data.
Power BI Security
Power BI offers granular control over data access through row-level security (RLS). Datasets can have role definitions that restrict rows a user can view.
For example, regional managers might get rows only for their region. Or a human resources role could limit employee data to only direct reports.
When applying RLS roles, filters are automatically added behind the scenes. Users only see permitted rows, but can still interact with reports freely.
RLS roles make it easy to limit access to sensitive data like salaries or customer contact info. Power BI allows wide report distribution without exposing data people shouldn't see.
Excel has very basic native security controls. Workbooks can be password protected, but anyone with access can view all data.
Excel does not support row-level security. The only option is to manually filter datasets, which requires maintaining separate spreadsheet files for each user or group.
For enterprise use cases, Power BI is the clear security winner. Sophisticated RLS policies can restrict access to sensitive data sets while maintaining full report interactivity. Excel lacks equivalent row-level protections.
Sharing and Embedding Content
Delivering insights through BI tools means getting reports and dashboards to stakeholders that need them. Here we compare sharing capabilities.
Power BI Sharing
Power BI offers extensive options for content distribution and collaboration. Within a company, you can publish reports to the cloud-based Power BI service.
Coworkers can easily discover and view reports based on permissions. The Power BI mobile app makes reports accessible on any device.
For external sharing, Power BI lets you embed reports on public websites or generate PDF snapshots. You can share read-only report access without exposing the full dataset.
Most powerful is Power BI's ability to embed interactive reports directly into other applications. For example, you can insert live reports into PowerPoint presentations.
This means presenting alongside up-to-the-minute data. As you discuss metrics, you can filter and drill down to answer questions immediately.
Sharing Excel content relies primarily on email attachments, shared drives, or OneDrive distribution. All require recipients to open the entire spreadsheet file, exposing the raw dataset.
Excel reports can be viewed in web browsers using Office Online or in the mobile app, but interactivity is limited. There are no native options for embedding Excel data visualizations live into other tools.
For a modern BI platform, collaboration and sharing capabilities are crucial. Power BI offers far more flexibility than Excel to distribute reports through multiple channels, applications, and devices while maintaining security.
Mobile Business Intelligence
Another key consideration today is mobile analytics. Many users need data on the go using phones or tablets.
Power BI Mobile App
Power BI offers a fully-featured mobile app optimized for touch and small screens. Dashboards and reports look great on mobile devices without any custom work needed.
On the Power BI mobile app, reports maintain full interactivity. You can drill, filter, slice, and dive deep into data on a phone or tablet.
For authoring, the mobile app includes a built-in report editor so you can build new reports directly on mobile devices. Overall, the experience feels responsive and natural on mobile.
Excel Mobile App
Excel also has a mobile app, but the experience is limited for business intelligence. Touch interactions like filtering and scrolling are rough and unintuitive.
And without adaptable formatting, Excel canvases fail to fit small touchscreens well. Zooming causes information loss as screen real estate shrinks.
Any mistakes made while interacting with Excel reports on mobile can corrupt the original file since the mobile app is not the native environment. For BI, Excel’s mobile capabilities lag well behind Power BI.
For today's mobile workforce, Power BI is the decisive winner. The mobile experience feels fluid and natural, critical for data insights on the go. Excel tends to struggle on smaller touchscreens.
Data Refresh and Updates
Now let's examine how Excel and Power BI handle data refreshes. Stale data leads to inaccurate reporting, so refresh processes must be robust.
Power BI Refreshes
Power BI makes scheduling data refreshes simple through auto-refresh. With just a few clicks, you can enable automatic refreshes daily, hourly, or by whatever cadence you need.
Behind the scenes, Power BI will pull the latest data from connected sources on the defined schedule. Users don't have to manually refresh—it happens automatically.
For live data, Power BI has Streaming Datasets. You can push data directly to Streaming Sets from tools like Power Automate. The visualizations update in real time as the underlying dataset changes.
In Excel, the common approach is data connections. Queries pull data from sources into the spreadsheet to be analyzed locally.
Refreshes require manually clicking "Refresh All" to fetch updated data. Automating this process requires building macros or Power Automate flows for each spreadsheet.
There is no native auto-refresh option in Excel itself. The manual process grows tedious with large collections of frequently changing Excel reports.
With robust refresh services like auto-refresh and streaming data built-in, Power BI is purpose-built for keeping datasets current. Excel's manual refresh process poses a far greater burden on users and IT to perpetually update reports.
The Bottom Line
Based on our in-depth comparison across six key criteria, Power BI proves superior to Excel for scalable, enterprise-grade business intelligence.
Here's a quick recap of the main points:
- Interactive reports - Power BI makes exploration easy with automatic cross-filtering. Excel requires manual report connections.
- Large datasets - Power BI handles millions of rows performantly. Excel bogs down beyond worksheets containing 1M rows, but can use Power Query to achieve similar performance.
- Row-level security - Power BI has sophisticated role-based security. Excel has none.
- Sharing and embedding - Power BI enables broad collaborative sharing. Excel is limited to files and attachments.
- Mobile - Power BI apps are designed for touch and mobile. Excel is difficult on smaller screens.
- Data refresh - Power BI has auto-refresh and streaming data built-in. Excel requires manual refreshes.
To be clear, Excel still plays an important role. It excels at lightweight modeling and analysis. For enterprise-scale business intelligence, Power BI is the leader in capabilities.
If you're looking to elevate your organization's analytics, Power BI is the best choice available. With outstanding performance and stunning interactivity, Power BI empowers your whole company to gain valuable insights from data.