I like how easy Microsoft Power BI makes it to visualize data and create interactive dashboards. It saves time on reporting, helps identify trends quickly, and makes it easier to share insights with others in the organization. These features help me quickly understand large amounts of data and spot trends that might otherwise be missed. The dashboards provide a clear view of key metrics, making reporting faster and helping the team make better decisions based on real-time information. Review collected by and hosted on G2.com.

Power BI is a great tool overall, but it can take time to learn some of the advanced features. Large reports can occasionally be slow, and certain features require additional licensing. 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.

Microsoft Power BI makes it easy to turn large amounts of data into clear, interactive dashboards and reports. I like how it connects to multiple data sources, provides powerful visualisations, and helps teams make data-driven decisions quickly. The integration with other Microsoft products such as Excel and Teams is also very useful. Review collected by and hosted on G2.com.

The learning curve can be quite steep for new users. Performance can sometimes slow down when handling very large datasets, and some advanced features require higher-tier licenses, which can increase costs for smaller businesses. Review collected by and hosted on G2.com.

So working as a Machine Learning Engineer at a medium-sized tech company, my main use case for Microsoft Power BI is being able to communicate between the complicated data models and non-tech business teams. I create visualizations of our model performance metrics, monitor data and feature drift over time using the software, and convert our predictions to interactive dashboards. I don't hand off raw data, but I provide cleaned and automated Power BI reports which the sales and marketing teams can interact with and understand.I really like the integration with my tech stack—the fact that our tech stack is already pretty Azure-heavy, and since we use Python extensively, seamless integration is a big plus, really. Being able to run a Python script right in the tool to do data processing before visualizing it is a huge timesaver for my workflow. In addition, the power of the DAX engine provides for extremely sophisticated aggregations and custom metrics on the fly. What it does do really is take raw machine learning outputs and turn them into easily understood, interactive story, so in meetings, I don't spend a ton of time explaining static charts, I spend a ton of time building and refining my models. Review collected by and hosted on G2.com.

The downside is that there are a couple things about it that are annoying. It is a desktop application and when I'm having to work with larger datasets locally, the software often becomes slow or even crashes completely. Moreover, DAX is a very powerful tool but is surprisingly complex and deep to learn, much more so than normal SQL or pandas. I also don't like the version control in the Power BI world very much. Being able to work with other engineers on the same dashboard file is a pain in the ass because it is not a collaborative file that can be easily worked on and shared using standard git workflows; it has to be passed back and forth by us manually. Review collected by and hosted on G2.com.

Some of my most time is spent developing models in Python and SQL but I have to be able to get those models to our executive team without overwhelming them with code. Power BI is amazing for this translation component! Integration of our current Microsoft stack, Azure and SQL Server is very seamless. What I like a lot is the intuitive way that interactive visuals are created once the data model is correctly configured. The cross-filtering facility is a very useful feature: it means that users who need to find information in the data but are not necessarily technical can do so without me having to write a thousand ad hoc queries each week. I also enjoy that when I need to create an extremely customizable visualization for which there isn't a native tool, I can simply embed my Python and R scripts directly within the dashboards. Review collected by and hosted on G2.com.

However, there are also some drawbacks to the platform. The challenge I think I am having the most difficulty with is DAX. Many people find DAX difficult to use, as they are used to working with Python and SQL which they find easier to use. You have to get up to speed on a language you never heard of in order to make a simple rolling average or running sum. The other primary concern is that of the performance of the desktop application. Power BI Desktop can be a huge memory consumer and occasionally consumes so much memory that it slows or even crashes, disrupting my workflow when working with larger datasets. Finally, no support for Apple Mac operating systems makes their usage extremely irritating to some of our team members, forcing them to use an inefficient virtual machine to create or edit a report. Review collected by and hosted on G2.com.

Actually I love how it makes it easy to run complex data into clear and interactive dashboards. I like how quickly I can connect different data sources and create reports so yaa I lovethis product Review collected by and hosted on G2.com.

I think when working with DAX formulas and advanced data modeling it can feel a bit complext other than that everything is good 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.