Microsoft Power BI Reviews & Product Details

The seamless integration with other Microsoft tools like Excel, Teams, and Azure makes Power BI incredibly convenient. The drag-and-drop interface allows non-technical users to build powerful dashboards quickly, while the DAX formula language gives analysts deep customization. Real-time data refresh and the ability to share reports across an organization without extra licensing costs are major advantages. Review collected by and hosted on G2.com.

The learning curve for DAX can be steep for new users, and the desktop app is Windows-only, which excludes Mac users from the full experience. Performance can slow down significantly with large datasets, and the UI can feel cluttered. Licensing costs also add up quickly when sharing reports with external stakeholders outside your organization.” Review collected by and hosted on G2.com.

I like the minimalistic interface of Microsoft Power BI. It's very straightforward, where it's just about adding the checkboxes and getting the data done. It also simplifies creating graphs and exporting the data for use in external tools. Review collected by and hosted on G2.com.

Sometimes when the data is vast, Microsoft Power BI tends to have so many options, and there's no feature for viewing operations within the dashboard, which makes it more complicated if the dataset size is huge. It's also very difficult to understand and navigate through the various options for each start. The initial setup isn't that easy because data needs to be stitched from multiple sources, making it difficult to centralize data into Power BI, as it's a very manual process. 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.

One of the aspects I am particularly fond of is the dynamic integration with Fabric, which has greatly improved the way we do data engineering tasks and has allowed implementation to be faster than before due to less complex ETL. The Direct Lake mode is another game-changer for the professionals, providing instant performance on large volumes of data that we process frequently every day during reporting. The numerous features are impressive too, especially the Copilot for Power BI, which has simplified working with DAX and generating the narrative. In addition to this ease of use, the seamless integration with the M365 ecosystem and robust community and customer support ensure that we can resolve technical hurdles quickly. Review collected by and hosted on G2.com.

The Direct Query mode may be considered an absolute necessity for real-time analytics; however, it requires significant effort to improve its effectiveness in a cloud environment such as Snowflake. The main problem with Direct query mode is the delay in visualisation refresh of reports due to extra load in terms of metadata exchange and query transformation. Review collected by and hosted on G2.com.

The ability to connect data is really great. As a user, it’s fairly easy to navigate once you get the hang of it. It can feel daunting at first, but with minimal effort you start to understand the key features and feel comfortable pretty quickly. It helps us connect multiple data sets and sources using a primary key, similar to how you can in other tools, and it also lets you visualise the story behind the data. It really helps users paint a picture with the data. We use it very often to share key insights with both immediate and extended stakeholders. Review collected by and hosted on G2.com.

I’d love to see PowerBi offer data-prep and clean-up capabilities more in line with other tools. Ideally, when I load a file, it would proactively flag issues to fix, instead of being so strict about the source dataset needing to be structured a certain way with data types already clearly defined. As it stands, changing data types can be time-consuming, and the same goes for handling NULL values (or cases where zero values should really be treated as NULL, etc.).

I also find it can be fairly resource-intensive, especially for users who aren’t very familiar with data-flow optimisations. On top of that, there are some logical inconsistencies that raise the barrier to entry and make scaling the product harder. For example, matching on duplicates is case-sensitive in certain parts of the tool but not in others. That can let something pass initial checks, only to fail later when you start linking relationships.

Lastly, having the option to show grid-style visuals (even if that feels like something you’d normally do in Excel) would be genuinely helpful, and I think it would make the product more approachable for non-technical users and slower adopters as well. Review collected by and hosted on G2.com.

I like creating a federated data model as centralized, which helps to build shared reports on top of that, and RLS is helpful for working on finance and sales data using a centralized dataset and report. I also appreciate the Apps feature, which gives me freedom as a developer to satisfy client requirements. The paginated reports are useful for sending Excel outputs to specific user groups for their business needs. The federated data model minimizes the rework involved in data model development and reduces the number of standalone reports, allowing me to focus on report development instead of creating data models for each individual report. The initial setup of Microsoft Power BI was quite simple, not a big deal to set up the environment. Review collected by and hosted on G2.com.

I don't like that we can't edit the report measures in the service, even with admin level access. We're always dependent on the Power BI Desktop to update DAX. Also, if we use the Tabular Editor to edit, we can't download the file from the service. Review collected by and hosted on G2.com.

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.