Microsoft Power BI Reviews

I've been using it for financial data.

Flexibility and usefulness of the data.

Trend data and dashboards need improvement.

I have been using Microsoft Power BI for some time. 

The stability is a seven out of ten. 

The initial setup is straightforward. 

Overall, I would rate the solution a seven out of ten. 

I use this solution for activity reporting.

The solution makes it easy for me to develop reports and publish them. Additionally, it effectively supports communication or data diffusion.

I have used the solution for five years.

I have observed issues regarding stability.

I have found that some issues exist, indicating room for improvement in scalability.

I rate the customer service a seven out of ten.

Neutral

The initial setup was easy.

The implementation required only one team.

I have seen some cost savings, however, overall, I have not experienced a return on investment.

I found the setup cost to be expensive, and rate it at seven out of ten also.

SAP Business Object is considered an alternative.

Overall, I rate the product an eight out of ten.

We use Microsoft Power BI for both data manipulation and visualization, with a strong emphasis on data-driven storytelling. It allows you to clean and transform data. You can connect to various data sources, such as Excel, SQL databases, and SharePoint files, and clean and prepare your data using Power Query. Additionally, you can write DAX to create powerful measures for diverse use cases. Power BI enables the creation of highly insightful dashboards to convey information.

The data manipulation and data cleaning tasks are handled in the backend by Power Query in Microsoft Power BI.

Integrating data from multiple sources in Microsoft Power BI is very easy. For example, you can connect to SharePoint, various SQL servers, and other platforms. Power BI also offers a range of connectors and libraries for integrating data from various sources, including databases, online services, and cloud-based platforms. It saves a lot of time by handling large datasets. It can process millions of rows of data and allows users to create visualizations and analyze trends quickly. Power BI is effective for various types of data analysis and can adapt to complex data needs.

Additional features can enhance Power BI's capabilities in predictive analysis. Currently, Microsoft Fabric is integrated with Power BI. As Copilot and further integrations continue to develop, they will enhance Power BI's functionality.

It offers a range of formatting options for reports and dashboards. For example, if you have multiple headers and change one header's color, all the subheadings can automatically adopt the same color. This feature allows for extensive customization and formatting, which is important because leaders often prefer color-coded information presented in a specific manner.

I have been using Microsoft Power BI for seven years.

I rate the solution’s stability a ten out of ten.

More than 400 people utilize it. It is suitable for small and medium businesses.

You can create dashboards using Power BI Desktop and share the Power BI Desktop file itself. However, for larger organizations, Power BI offers a web-based solution through Power BI Service, where you can publish reports and dashboards.

I rate the solution’s scalability a ten out of ten.

Microsoft offers excellent products, and its community provides many options and support. If users encounter specific issues, they can find solutions in various Microsoft communities.

I have experience with both Microsoft Power BI and Tableau. Working with Tableau posed multiple challenges, such as data integration and ETL, which can be quite complex. Additionally, Tableau's measures and visualizations can be somewhat intricate. However, the flexibility in Power BI is comparable to that of Tableau.

I used Tableau for about five years before switching to Power BI, so I have a total of around eleven years of experience with these tools. As an advanced Tableau user, Power BI is simpler in comparison. Additionally, Tableau requires a paid license, whereas Power BI does not require a purchase unless you deploy it.

The initial setup is simple. You can start in about twenty minutes. However, you'll need to thoroughly understand the application to gain deeper and more critical insights. While you can learn the basics within a few hours, mastering the more advanced features involves a steeper learning curve.

Compared to other solutions, it can be relatively expensive, while the cost can be more manageable for organizations, considering the scale and the benefits.

Power BI offers several built-in AI capabilities. For instance, it includes features for sentiment analysis, generating word clouds, pattern recognition, and trend analysis. While Power BI integrates well with various external data sources and services, including advanced AI models, many analytical functions are available directly within the Power BI suite.

Overall, I rate the solution a ten out of ten.

We use Microsoft Power BI to manage and visualize the control of permits to work for service companies in industrial plants in Mexico. The control of permits is crucial because all service companies must be registered with a special number by the government, and all personnel must be certified for the specific work they will perform inside the plant. For example, if installing cameras at a high level, you need a permit for that specific condition, which has specific rules to comply with to carry out the job. In Power BI, we can visualize the number of permits, open permits, closed permits, refused permits, and all types of permits we have. This allows us to manage all permits for people working on various projects inside the industrial site.

The most valuable aspect of Microsoft Power BI in my field is the insights it provides from analyzing data. Sometimes, these insights go beyond what traditional analysis can reveal due to the large volume of data involved. In terms of improving our data analysis process, it starts with identifying data sources, followed by cleaning and filtering out irrelevant data. Then, we categorize and structure the data to achieve the best visualization and insights.

Regarding Power BI's integration with other tools, although we haven't implemented it ourselves, it's known that Power BI can integrate with systems like SAP or ERP software, which could enhance our analytics capabilities if needed.

I believe Power BI could improve by making data tables and databases easier to handle, especially for non-programmers who may not be familiar with languages like Python. Simplifying these aspects would enhance the usability and accessibility of Power BI for a broader range of users.

I have been using Power BI for the last six months.

In terms of stability, it's been reliable. We haven't encountered any bugs or crashes.

We've definitely seen a return on investment. We calculated the benefits and ROI for our solution.

Regarding cost, the initial investment wasn't too high, but ongoing licensing could add up.

Overall, I'd rate Power BI as an eight out of ten. It's been quite effective for us.

We use the solution for data analysis. 

The tool's most valuable features are slicer and Microsoft Copilot integration. It also allows users to see reports on mobile devices. The solution can also integrate with various data sources. 

The limitations within Microsoft Power BI include the volume of data it can handle, as there's a cap on the number of rows you can keep. When you pull your data and build your models, you're restricted by this row limit. Additionally, certain SSRS features are deprecated, which can be a drawback for users who rely on those capabilities.

I have been working with the product for three to four years. 

I rate the solution's stability a seven out of ten. It has limitations on rows, datasets, and the things that can add to the memory. 

I rate the product's scalability a ten out of ten. It is resilient and scalable. 

I am a technical supporter and can support myself. 

Before Microsoft Power BI, we used Reporting Services. We switched to it because it is part of Microsoft's ecosystem, and Microsoft has mapped the roadmap for visualization from SSRS to Microsoft Power BI.

I rate the solution's deployment ease a ten out of ten. It is easy and can take around 14 hours to complete. 

Microsoft Power BI's deployment was done in-house. 

The solution's pricing is medium.

I would recommend Microsoft Power BI based on the use cases. I rate it a seven out of ten. 

I use the platform primarily to create visualizations and reports from data to gain insights. It is utilized for operational, decision-making, and managerial reports.

The product's most valuable features are DAX functions for formulas and calculations.

I would suggest improvements in visualization standards, particularly in customization and appearance, to match tools like Tableau.

I have been working with Microsoft Power BI for two years.

I rate the platform stability a seven and a half or eight out of ten. 

The product is suitable for medium-sized companies with straightforward requirements. It can handle thousands of users, but its effectiveness depends on the data volume and reporting needs.

I rate the scalability an eight. 

The technical support team's response quality can vary based on the engineer's expertise and availability.

Power BI is more cost-effective, whereas Tableau provides more advanced features and higher-quality visualizations. For critical business needs and high data volumes, Tableau might be more suitable. 

The initial setup process is simple. 

I have worked with both the cloud version and the desktop model. Each has its advantages depending on the need for high-quality visualizations or the volume of data.

I rate the product pricing a ten. 

The solution supports integration from various applications well enough to meet most business requirements. 

I rate it a nine out of ten. 

In terms of impact, Power BI significantly improved decision-making and instilled confidence in our data. It also resulted in cost savings by avoiding the purchase of expensive Oracle integration tools like ODI. These savings were crucial for our fast-growing company, allowing scalability without increasing expenditure.

The most effective feature of Microsoft Power BI for data analysis is the ability to use Power Query directly from Excel. Power BI's integration capabilities impacted our data management by allowing us to push all reporting down to the end user, giving them the capability to perform "what if" scenarios and discover and validate their own data without needing to refer to IT. Additionally, it provided insights that we couldn't get from Oracle Cloud. We wrote an extract routine to transfer our Oracle Cloud database to Power BI, which was a game changer in terms of giving people confidence in the finances.

It was easy to implement Microsoft Power BI into our existing infrastructure, but integrating it with Oracle Cloud was very difficult. The integration with Oracle Cloud required us to build a sophisticated database replication process because the APIs for Oracle Cloud are very restricted in terms of volume, depth, and complexity of queries. However, the part of implementing Power BI into our infrastructure was very easy. It required almost no tech input because it was all part of Office 365. To overcome the integration issues, we developed an extract and update process, although it was quite complicated and involved a lot of IP.

Power BI excels in integrations and its ability to handle various data sources. It would be beneficial if it could integrate more seamlessly with cloud interfaces like Oracle Cloud, although I understand the challenges with Oracle's policies on database access. Another area for improvement would be enhancing error messaging, especially when working with Dataverse and M Code for automation.

I have been using Microsoft Power BI for the past ten years.

I would rate Power BI overall as an eight. It's a very powerful tool for users, which I appreciate. However, there are some areas that could be improved.

As for AI-driven decision processes, I believe Power BI supports them, although we haven't utilized those features ourselves.

Power BI is primarily utilized for seamlessly integrating data from diverse sources and streamlining their analysis. Its secondary function is to facilitate the effortless creation of reports and dashboards.

Power BI has significantly enhanced our data analysis and visualization capabilities, showcasing its versatility. It seamlessly connects to a multitude of data sources, ranging from traditional databases to diverse formats such as flat files and specialized systems like ERP and SharePoint. Additionally, Power BI's transformation language, known as the M language, is remarkably flexible and user-friendly, empowering users to efficiently analyze and merge data sets.

The architecture of Power BI, including its dashboards and data refreshing capabilities, is becoming increasingly sophisticated. Particularly in the Azure environment, it offers enhanced power but also complexity. Managing this complexity can be challenging, requiring a skilled team to configure the tool and handle data transformations.

Integrating Power BI with other applications and services offers numerous benefits. It serves as a powerful tool for gathering analytics from diverse data sources or applications, providing quick access to analytical capabilities ranging from simple data slicing and dicing to advanced data science tasks. Power BI seamlessly integrates with data science tools like Python, enabling enhanced functionality. While its built-in charting capabilities may not be as extensive as some competitors, there's an ecosystem of add-ons and partner products available. Additionally, Power BI offers an open customization programming framework, allowing users to create custom features when needed.

The greatest value of Power BI lies in its ability to integrate data into a single platform, facilitating analysis with ease. This makes it ideal for proof of concept and launching initiatives, as tangible results can be achieved quickly. Power BI offers a straightforward path to generating multiple insights, providing a fast and efficient tool for obtaining actionable results.

The robust connectivity is a key strength of Power BI. The ease of integration and connectivity stands out as the most critical aspect, followed closely by the flexibility to customize reports and dashboards.

There needs to be improved guidance and documentation for the initial setup of Power BI as it currently remains complex. While the current setup process is not necessarily bad, investing effort in this area will be beneficial given the challenges involved. Additionally, with Azure itself evolving into a sophisticated and complex platform, coupled with the integration of various analytics tools within the Microsoft ecosystem, challenges arise from multiple fronts.

Another aspect worth mentioning is data transformation integration. Currently, there are multiple approaches to data transformation on Azure, including Azure Data Factory, Data Lake, Power BI's data transformation capabilities, and data flows. The abundance of these approaches can lead to complexity, and there may be benefits to converging them into a more integrated solution.

I have been using it for four years.

It is much more stable compared to ten years ago.

It is scalable, but achieving scalability necessitates subscribing to higher tiers of the product.

In terms of technical support, although I didn't directly interact, the team I collaborated with frequently contacted support and reported issues, which were promptly addressed. Leveraging the partnership level of your company can significantly assist in this process. Given the large user base of the product, it's crucial to maintain close communication with support to ensure that issues are resolved effectively.

In my previous experience, I had some exposure to SAP Business Objects. At that time, around ten years ago, the main differentiators were the pricing and the integration with Office tools and data sources, making it stand out in the realm of BI.

The initial setup of Power BI can be complex. Currently, Microsoft is attempting to combine various historical approaches and keep them available, which can lead to confusion about which path to take. Power BI is now becoming an integral part of Microsoft's overall ecosystem, adding to its complexity. While this integration provides additional features, it may also pose challenges for new users navigating through the layers of Power BI's capabilities.

Deployment and maintenance can be efficiently handled by a small team of two skilled engineers. With adequate rights to administer both the core BI services and supporting Azure services, two people can accomplish a significant amount of work.

Subscribing to Power BI entails various payment options, including different tiers of subscriptions, some of which can be quite costly. However, there is also a free tier available. Additionally, Power BI licensing may be bundled with Office or Microsoft 365 subscriptions, offering different levels of partial licensing based on your Office 365 subscription. Microsoft emphasizes bundling licensing to make it more appealing to users. While Power BI is generally a paid product, particularly for enterprise features and scalability, you can start with the free version and still achieve significant functionality.

I would suggest starting with Power BI for an easy entry into business intelligence and analytics. As you gain experience, you can assess whether customizing the platform or utilizing partner components suits your needs. Alternatively, you can compare it with other products that may require deeper learning or higher entry levels. Overall, I would rate it eight out of ten.