Microsoft Power BI Reviews & Product Details

The ability to integrate data from multiple sources into one view or dashboard that is readily available for program analysis. TThe various reports and dashboards provide a multifaceted view of the program for more effective/accurate analysis and decisions. Review collected by and hosted on G2.com.

There's a big learning curve if you aren't formally trained and a significant technical gap in access and knowledge between business customer (e.g. a business unit or department) and developers. This sometimes makes it frustrating to resolve issues because they're on the configuration side which business users don't have direct access to. This isn't an issue if developers and data services teams are immediately and easily available (in-house) but can be very challenging if you have to go through some hoops for this kind of support. Review collected by and hosted on G2.com.

What I like best about Microsoft Power BI is its ability to transform raw data into interactive and visually appealing dashboards. It makes data analysis easier by providing powerful visualization tools, real-time insights, and seamless integration with Excel and other data sources. I also find it very useful for creating reports that help in better decision-making and presenting data in a clear, structured way. Review collected by and hosted on G2.com.

One thing I dislike about Microsoft Power BI is that it can have a learning curve, especially for beginners who are new to data modeling and DAX. Sometimes performance may slow down when working with very large datasets. Review collected by and hosted on G2.com.

As a Senior Data Analyst with 3.5+ years of experience, what I value most about Power BI is its seamless integration with the Microsoft ecosystem (Azure, SQL Server, Excel). The Power Query Editor is a real lifesaver when it comes to data cleaning and preparation. In particular, being able to write complex DAX measures helps me manage intricate financial calculations—such as YOY growth and risk metrics—and then present them clearly through interactive dashboards that stakeholders can explore. Review collected by and hosted on G2.com.

The learning curve for advanced DAX can feel quite steep, especially for beginners. I’ve also noticed performance slowdowns when working with very large, unoptimized datasets (multi-million rows) or with complex star schemas. And while the formatting options for visuals have improved, they still feel somewhat restrictive compared with specialized design tools like Figma. Review collected by and hosted on G2.com.

I liked how Microsoft Power BI makes data visualization quick and accessible, especially for users already familiar with the Microsoft ecosystem. Its seamless integration with Excel and other Microsoft tools helped us build dashboards rapidly without a steep learning curve. The drag-and-drop interface and strong data modeling capabilities made it easy to turn raw data into meaningful insights.

However, as our data complexity grew, we eventually transitioned to Tableau for more advanced visualization flexibility and performance with large datasets. Still, Power BI remains a great starting point for organizations looking for cost-effective and user-friendly BI solutions. Review collected by and hosted on G2.com.

One of the key challenges we experienced with Microsoft Power BI was its limitation in handling highly complex and large-scale datasets efficiently. While it performs well for standard reporting and moderately sized data, we noticed performance slowdowns when working with more advanced analytics and larger data models. Additionally, customization of visuals, although possible, often felt restrictive compared to more specialized BI tools, especially when we needed highly interactive and visually rich dashboards.

Another area we found less convenient was the dependency on DAX for advanced calculations, which has a learning curve and can make maintenance difficult for larger projects. Managing and optimizing reports across teams also required careful structuring, as scalability was not always seamless.

As our business needs evolved toward deeper analytics and more flexible visualization capabilities, we transitioned to Tableau. It provided us with greater freedom in designing complex dashboards and handled larger datasets more smoothly. That said, Power BI is still a solid choice for organizations looking for tight integration with the Microsoft ecosystem and cost-effective reporting solutions. Review collected by and hosted on G2.com.

power bi is a very easy to use tool. it was very easy to build charts and build dashboards. it is very flexible to adjust chart sizes in the dashboards. it can be integrated with various data source tools. its calculations are also very fast and efficient and hence improves performance of the dashboard. its recent integrations with mcp has improved it ai features as well. Review collected by and hosted on G2.com.

some of the features like dynamic zone visibility has to be done using bookmarks which takes up a lot of time and effort. some of the dax calculations are too complex to build. Review collected by and hosted on G2.com.

I’ve been using Microsoft Power BI mainly for reporting and dashboard creation. In one of our projects we connected Power BI directly to warehouse tables and views in Microsoft Fabric, and the experience was pretty smooth.

What I like most is how quickly you can turn structured data into a dashboard. Once the connection with the warehouse is set up, creating visuals like charts, KPIs, and filters is quite straightforward. Business users in our team prefer dashboards over raw tables, so Power BI helps a lot in presenting the data in a clear way.

Another thing I find helpful is Power Query for simple transformations. Even if the data is mostly prepared in the warehouse, sometimes small adjustments are needed and Power BI handles that well. Review collected by and hosted on G2.com.

When reports start getting bigger with many visuals, performance can sometimes slow down a bit. It usually works fine but you need to design the model carefully if the dataset grows.

Also, learning DAX properly takes some time. Basic reports are easy, but advanced calculations definitely require practice. Review collected by and hosted on G2.com.

The most convenient and intelligent BI tool with excellent reporting features and ability to manage data - model - report. Easy publishing to Server and communicate with AI using copilot Review collected by and hosted on G2.com.

Connectors / managing live connection to databases can sometime be tedious .

Slicers and filters related to worksheets can sometime not sync Review collected by and hosted on G2.com.

I love using Microsoft Power BI for its interactive dashboards, which help me track my business performance and enhance my decision-making abilities. The automation of my reporting strategies is a huge plus. DAX, or Data Analysis Expressions, is extremely useful for custom calculations and makes complex tasks like measuring year-over-year growth easier. I appreciate the automatic sync feature as it saves me from having to manually update files all the time, it’s efficient to just refresh and see all the updates. The initial setup was very straightforward, I'd give it a 9 out of 10. Review collected by and hosted on G2.com.

It gets slower sometimes when I'm working in the integration of multiple datasets. Connecting multiple data sources is difficult if the formats of both have a lot of discrepancies, and it also slows down the reports. Review collected by and hosted on G2.com.

One of the best things about Power BI is how intuitive it is. Even without formal training, I was able to start building dashboards right away. Creating charts is incredibly easy, and the final result looks very professional and visually appealing. It’s a great tool for presenting data to stakeholders who value clarity and design. Review collected by and hosted on G2.com.

The Login Process: Accessing the user account involves too many steps, which can be frustrating.

Limited Presentation Mode: It’s disappointing that the presentation mode is only available on the web version. Because of this, I usually end up sharing my reports in PDF format when sending them to others. Review collected by and hosted on G2.com.

One of the greatest strengths of Power BI is its seamless integration into the Microsoft ecosystem. For an analyst already working within Azure, SQL Server, or even just Excel, the connectivity is unmatched. It’s not just about moving data; it’s about the familiarity of the interface and the ease with which you can publish reports to Teams or SharePoint. Furthermore, the breadth of visualizations—both native and community-created—allows me to tell a compelling story that resonates with stakeholders, regardless of their technical literacy.

The true magic, however, happens when you have a well-constructed semantic model. When the backend logic is solid, the "drag-and-drop" simplicity of the front end is incredible. It empowers business users to perform their own ad-hoc analysis and build their own reports on top of the data model I’ve created. This self-service capability is a win-win: users get their answers faster, and I can focus on deep-dive analytics rather than tweaking minor chart formatting for every request. Review collected by and hosted on G2.com.

The biggest “trap” for beginners is definitely DAX. At first glance, it looks just like Excel formulas, which is really misleading. In reality, it’s a completely different animal. The underlying logic is fairly complex, and it’s very easy for a newcomer to get overwhelmed—or, even worse, to calculate something incorrectly because they didn’t understand the formula’s “context.” It’s a steep hill to climb before you start feeling confident with it. Review collected by and hosted on G2.com.