Power BI vs Excel: Time to Make the Switch?

From startups to multinationals, Microsoft Excel is at the core of countless organizations’ data analysis and decision-making processes, with the Association for Financial Professionals (AFP) noting that 70% of all companies “rely heavily” on spreadsheets for financial activities.

On its own, Excel may not be enough, especially for FP&A processes requiring access to multiple sources of complex external data. Similarly, while Power BI is a robust reporting tool, it isn’t as familiar to most people.

So how do you know which is right for your situation? Let’s walk through their key features and limitations, along with some suggestions for ways to make the most of both tools.

Is Power BI the Same as Excel?

While Excel and Power BI have some overlapping functionality and are both from Microsoft, they definitely aren’t the same. They each serve different purposes and have distinct strengths. Many people use both: Excel for initial data manipulation and ad-hoc analysis, and Power BI for creating insightful reports and visualizations from larger datasets. This way, you leverage the best of both tools for more effective data analysis.

Comparing Key Capabilities of Excel and Power BI

In the Excel vs. Power BI debate, it’s essential to recognize that both tools can analyze various datasets and present the information in tables, visual charts, and graphs.

Excel’s appeal comes from its simplicity, familiarity, and cost-effectiveness, making it a staple for ad hoc analysis with custom formulas and charts. However, it’s not designed to handle large datasets. On average, even medium-sized organizations gather data from more than 400 sources for business intelligence. Managing even a portion of these sources in Excel can lead to trouble.

In contrast, Power BI is gaining traction for its interactive, real-time business intelligence and scalable data visualization. Its drag-and-drop interface simplifies creation of interactive dashboards, offering advanced visualization and easier sharing across large organizations.

Imagine you’re working on a project involving lots of data analysis. You start with Excel, a versatile spreadsheet program that’s great for data entry, calculations, and initial analysis. You can manipulate data and perform ad-hoc analysis with ease, thanks to Excel’s familiar interface and formulas. However, you hit a snag when your dataset grows too large, as Excel can only handle about a million rows. Plus, you may want to create more engaging visualizations than Excel’s basic charts and graphs.

This is where Power BI comes in. Unlike Excel, Power BI is specifically designed for business intelligence and data visualization. It can handle massive datasets, connecting to a wide range of data sources, including cloud services. With Power BI, you create advanced, interactive visualizations that bring your data to life. It’s also excellent for creating reports and dashboards, offering cloud-based sharing and real-time collaboration features.

Key Capabilities	Excel	Power BI
Data Model Types	Supports full relational model.	Supports full relational model.
Data Model Limits and Storage	Limited by worksheet rows or the local data model. Users can’t access the data model outside the workbook.	No limits in DirectQuery mode. Deploying models to the Power BI service enables an authentic client-server architecture, making models accessible to other clients, such as Excel.
Automated Data Model Generation	Requires expertise or ready-made data models from solutions like Acterys Apps.	Requires expertise or ready-made data models from solutions like Acterys Apps.
Data Source Integration	Native connectivity to import data from various sources. No DirectQuery connection type.	Supports connectivity with hundreds of databases, cloud services and more. DirectQuery provides a live connection to a source.
Logic	Uses DAX language.	Uses DAX language.
Security	Standard security features and file-level protection, but limited granular security.	Power BI Server offers granular security rights using Row Level Security (RLS). No data is stored in Power BI in Direct Query mode.
Live Data Streaming	No easy way to refresh data automatically.	Offers live streaming services and automatic refresh settings.
Large Datasets	Suitable for smaller datasets, more limited with larger datasets.	Specifically built to handle big data — can process billions of records.
Data Security and Governance Policies	Limited data security features.	Offers cloud-based security provisions and aligns with governance policies, even when data is exported.
Accessibility and Collaboration	Provides live collaboration and sharing capabilities, such as Microsoft Teams integration.	Offers comprehensive publishing options through Power BI Service, including embedding dashboards on websites and automatically refreshing data.
Write-Back and Planning	Data written back is stored in the workbook. Can be extended with add-on solutions like Acterys.	Doesn’t offer write-back options by default. Can be extended with add-on solutions like Acterys.
Critical KPIs and Metrics	No notifications or alerts for specific metrics or KPIs.	Allows setting notifications and alerts for proactive monitoring.
Learning Curve and Usability	Familiar interface, easy to use for basic tasks.	Intuitive drag-and-drop interface for building dashboards and reports.

Data Model Types

Start your reporting or analysis by building a data model that optimizes the data for the analysis process and integrates different sources. The Power Query data modeling feature is available in Excel and Power BI but works with slight differences across the platforms.

One key distinction between Power BI and Excel is in the structure of the data model, which can have a significant impact if you’re working with a single table versus a comprehensive model with relationships between tables.

Excel (with the Excel add-in, Power Pivot) and Power BI (Analysis Service) support a full relational model, commonly called a star schema, where data is organized into a central fact table surrounded by dimension tables, forming a star-like structure. This capability sets Excel and Power BI apart from tools like Google Sheets, which need similar functionality.

Data Model Limits and Storage

The data model tables in Excel are limited by the number of Excel worksheet rows or the limitations of the local data model, Power Pivot, associated with the workbook. The data model in Excel is also limited to use within the workbook itself, without support for client-server functionality, meaning users cannot access the data model outside of the workbook.

For local requirements, Power BI Desktop also uses a local analysis services instance as the data storage engine in import mode. There are limitations similar to Excel in this mode, but in live connect DirectQuery mode, there are no such limits. Power BI Desktop allows users to deploy the data model to the Power BI service, enabling an authentic client-server architecture. This means that the model becomes accessible to other clients, such as other Power BI reports or even Excel.

Automated Data Model Generation

Designing an effective data model can be a very complex task that requires significant expertise of the modeler, particularly in light of complex enterprise resource planning (ERP) systems and integrating other sources, such as customer relationship management (CRM) software or point-of-sale (POS) solutions, into one data model. Solutions like Acterys Apps offer readily available best practice data models, including Power BI and Excel reports, and can help streamline this process.

Data Source Integration

Excel has expanded its capabilities beyond simple copy-pasting to offer native connectivity for importing external data. With the Power Query feature, Excel can import data from various sources, including unstructured file formats, SQL and SAP databases, Azure Cloud and Power BI.

However, one notable difference between Excel and Power BI is the absence of the DirectQuery connection type in Excel’s standard Power Pivot data model. DirectQuery allows users to connect to a data source in real time, accessing the latest version of the data without physically moving it into the data model.

By contrast, Power BI supports connectivity with hundreds of databases, cloud services, flat files, apps, systems and more. It even supports DirectQuery, enabling users to create centralized dashboards that display business KPIs, market trends, forecast projections and other insights more visually and interactively.

While Excel’s Power Query has fewer connectors than Power BI, having a connector doesn’t automatically provide the ideal data model. Regardless of the tool chosen, you’ll still need to invest in designing the appropriate data model, integrating different data sources and establishing calculation logic.

Logic

Excel and Power BI use the Data Analysis eXpression (DAX) language to define calculation logic. DAX allows users to create customized formulas and perform aggregations, enabling the implementation of complex logic within and across tables.

The DAX language is a powerful feature shared by both platforms that offers lightning-fast calculation times, thanks to intelligent compression capabilities. This ensures efficient processing of calculations, even when dealing with large amounts of data.

Security

In Excel, standard security features are available to protect files and their contents. This includes file-level protection through encryption with a password, granting read-only access and controlling user actions within a spreadsheet. However, more than these security measures may be required for highly sensitive data, such as personal or credit information.

In practice, it’s rare for appropriate security measures to be adequately implemented for Excel workbooks. If someone gains access to the workbook, they have access to all the data, as there is no concept of granular security. This can pose a significant risk, especially when dealing with large datasets that anyone with access to the workbook can easily access.

In Power BI’s import mode, the security situation is similar to Excel. However, a distinct advantage emerges when deployed on the Power BI Server. Power BI Server allows for implementing granular security rights using Row Level Security (RLS). This means that exact security permissions can be defined, providing more control over data access.

In Direct Query mode, Power BI doesn’t store data internally. Instead, users must authenticate successfully with the underlying data source to access the data. This adds an extra layer of security, ensuring that only authorized users can retrieve the data.

Live Data Streaming

Some companies require time-sensitive data reporting. For example, the NYSE or London Stock Exchange can’t afford to work with outdated data, as the market conditions change by the minute.

Unfortunately, there’s no easy way to refresh data in Excel automatically. One approach is to use Visual Basic for Applications (VBA) and code to automate repetitive processes. This can quickly become time-consuming and overwhelming, especially when large datasets and multiple sources are involved.

Power BI, however, offers built-in features that make real-time data updates easy and manageable. It supports multiple methods for refreshing data, including:

• Live streaming services: Power BI allows you to set up live streaming services to update data continuously in real time.
• Automatic refresh settings: You can define intervals for automatic data refresh, ranging from every hour to as frequently as every second. You can also specify specific days and times for the refresh to occur.
• Change detection: Power BI offers a change detection feature where you can define a measure to check for changes in the data source. You can also specify how frequently the source should be checked for changes. However, this functionality is limited to DirectQuery sources and selected LiveConnect scenarios.

Large Datasets

Excel is a valuable analytics tool for storing and analyzing smaller datasets, typically with less than 1 million records or under a 500 MB workbook size. However, when handling larger datasets, Excel’s capabilities become limited. While Power Pivot can take significantly more data, such as hundreds of millions of rows, users may experience instabilities and performance issues, as Excel was not designed to be a big data store.

On the other hand, Power BI is specifically built to analyze data far beyond the limits of Excel. Power BI can process billions of records, making it suitable for enterprise environments that operate in fast-evolving and dynamic markets.

Its robust compression algorithms intelligently reduce data size and cache it on import, allowing for efficient storage and processing of large datasets. This adds immense value in enterprise environments where handling big data is crucial for making informed decisions.

Data Security and Governance Policies

Excel does provide password protection for workbooks and worksheets, but it lacks more granular security features. Power BI offers cloud-based security provisions that allow IT administrators to improve organizational oversight. This includes role-based authentication, which enables organizations to control who can view and edit reports, and row-level security, allowing organizations to restrict access to specific reports or data model areas.

Regarding governance policies, Power BI offers more comprehensive options than Excel. Power BI allows organizations to apply governance policies even when data is exported from the platform. This ensures that sensitive data remains protected outside the Power BI environment.

Power BI also enables the addition of sensitive content labels to critical data, providing an extra layer of security. It also includes session monitoring, allowing organizations to track user activity in real-time and identify suspicious or unauthorized actions.

Accessibility and Team Collaboration

Excel provides live collaboration and sharing capabilities, such as Excel Online in the web browser and integration with Microsoft Teams. While these features enable real-time collaboration, they can become challenging to manage in an enterprise setting. With numerous Excel files scattered across cloud storage platforms like SharePoint, extracting insights and effectively collaborating on projects can be difficult.
On the other hand, Power BI offers comprehensive collaboration options, mainly through the Power BI Service. Power BI Desktop and the ability to publish to the web are free, but they may not be ideal from a security perspective. The Power BI Service is the recommended solution for secure sharing with granular security controls.

The Power BI Service allows users to publish data to their desired destination, whether it’s single reports or dashboards. These can be shared within dedicated Workspaces, enabling a group of people to access and collaborate on the content simultaneously. The added benefit is that once you’ve published your content, the service will refresh the data automatically, saving you from resharing it repeatedly.

The Power BI Service also allows for embedding dashboards on online portals and websites. This feature provides viewers with interactive charts and graphs, allowing them to drill down into the data just as they would within the Power BI app.

Write-Back and Planning

Data written back in Excel is stored in the workbook by default, which isn’t optimal for analytics, reuse in other reports and tools or for security and data sharing purposes. Instead, a central database is a much better option. While Power BI also doesn’t offer write-back options by default, both solutions can be extended with add-on solutions like Acterys.

Acterys provides automatically generated data models from commonly used accounting, ERP, and SaaS solutions. It also offers tools to easily create data models from any data source. This data is stored in a standard SQL database in the cloud, which is already the standard in many organizations. Extensive planning, forecasting, and collaborative write-back options are available with eight custom visuals in Power BI or an add-on that works in the Excel Desktop version and Excel Online.

Critical KPIs and Metrics

The key to success in today’s hypercompetitive markets is the ability to react to change and do it fast. Power BI allows setting notifications and alerts when specific metrics or KPIs go below, above, or hit a set threshold. These notifications can be received through the Power BI app and via email, enabling users to proactively address issues before escalating.

For example, if you want to cap a marketing campaign’s spending at $10,000, you can use Power BI to set up an email alert that notifies you when spend nears or reaches that threshold. This allows you to closely monitor your budget and evaluate areas where spending is high, enabling you to optimize your expenses accordingly.

By contrast, Excel doesn’t offer this feature, making it more challenging to monitor and manage critical KPIs and metrics proactively. Users may miss essential changes or exceed thresholds without timely intervention and setting notifications and alerts.

Learning Curve and Usability

As a part of the Microsoft Office suite for decades, Excel has a significant advantage regarding user familiarity and ease of use. With multiple generations of users already accustomed to its interface, Excel offers a straightforward and intuitive experience. Users can quickly implement processes such as using mathematical formulas on datasets, building pivot tables, and creating graphs.

Power BI provides a drag-and-drop interface that simplifies building dashboards and reports. This intuitive interface makes it easy and enjoyable for users to create appealing visualizations.

However, to unlock the true power of both tools, you’ll need to dive deeper into advanced features, such as Power Query, setting up different visuals, and assessing the data refreshing and sharing processes.

Finding the Best Option for Your Use Case

Both Excel and Power BI offer unique benefits for financial analysis, reporting, and data visualization. While Excel’s familiarity and flexibility make it an invaluable tool for ad hoc analysis, Power BI provides advanced features tailored for larger datasets, real-time business intelligence, and more robust security and collaboration. But what if you could have the best of both worlds?

That’s where Smart XL comes in. Smart XL delivers a complete Excel-like experience with advanced analytics, data visualization, and live data access. It integrates seamlessly with both Excel and Power BI, combining Excel’s flexibility with Power BI’s powerful features. With Smart XL, you can simplify your data processes, streamline planning and forecasting, and collaborate efficiently.

Ready to transform your reporting and analytics experience? Explore Smart XL or visit Microsoft AppSource to purchase it directly and start using it today!