Microsoft Power BI Reviews

We have a lot of data, which we process and analyze using Python. Once the data is processed, we feed it into Power BI. In Power BI, we build dashboards and visualizations. Our team or customers can then view these dashboards.

Data visualization is crucial because while some people understand data, many find raw numbers or text difficult to interpret. Visualization makes patterns and insights clearer and easier to understand. Tools like Microsoft Power BI and Tableau are excellent for creating these visualizations, helping users grasp better and analyze large datasets.

For example, the variety of chart types available in Power BI is somewhat limited. While you can choose from various charts like dial gauges, bar charts, and line charts, there aren't as many diverse options as you might need. Sometimes, you might look for additional chart types and find that they're not available for download from the Internet.

Another area for improvement is data refresh functionality. Even with a premium license, the refresh rate is limited to every 30 minutes. This can be restrictive if you need more frequent updates, such as every 10 or 15 minutes, or at specific times, like every Monday at 4:25 PM. The current options are typically every hour, every 30 minutes, or daily. This limitation can lead to inefficient resource use if your data only needs to be refreshed at specific times.

I have been using Microsoft Power BI for four years.

Initially, Microsoft Power BI can be quite complex. The Microsoft website does not always provide clear guidance, so you might need to watch numerous YouTube tutorials. The initial setup can be challenging, but using Power BI becomes much easier once you become familiar with the process.

Once you use Power BI, you must install or subscribe to the software and spend time exploring and working with your data. Becoming fully proficient and deploying your solutions effectively may take a few months.

ROI is really great.

Power BI pricing is generally considered more affordable than Tableau. There is a free version available for Power BI, and the Pro version costs around $20 per user per month. In contrast, Tableau's pricing can be higher, with a Creator license costing around $70 per user per month.

Compared to Tableau, Power BI is considered more affordable. While Tableau is often seen as more versatile and professional, making it suitable for advanced and complex data visualization needs, Power BI is a more accessible option for beginners or organizations starting with data visualization.

Microsoft Power BI is a user-friendly tool for creating dashboards and visualizations. It allows you to easily import data from Microsoft Excel or CSV files, which are common data storage formats. Once your data is imported into Power BI, you can create a variety of visualizations, including line charts, bar charts, and gauges, to present it effectively.

Many people turn to resources like Google searches and YouTube tutorials to learn how to use Power BI. Microsoft also offers extensive learning materials.

Power BI has some AI capabilities, but it's primarily a tool for data visualization. For more advanced AI and machine learning tasks, such as those involving neural networks or complex algorithms, many data scientists prefer to use Python and integrate their results into Power BI for visualization.

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

My work is more about providing security solutions for about three years, making this service available to end users.   

My scope of work involves making the Power BI solution available as a general product to end users, ensuring that relevant security solutions are enabled from an identity perspective, licensing perspective, and from data loss prevention (DLP) and data protection perspective.

I work for a bank, so we are a customer of these services. We serve internal customers by making these solutions available.

Power BI can connect to various data sources. Depending on the business users, some may be using it along with their Excel sheets. The data source could be just the Excel sheet or a comma-separated values (CSV) file, where they receive data in that format from whichever application it is, and then they feed it into Power BI. 

Based on the business, they would have created analytic reports, and they are able to produce insightful analytic reports on the fly, based on management, end user, or stakeholder requirements. 

Users connect to the data source, which could be coming from SQL, Excel sheets, their own applications like SaaS applications, internal HR solutions, the intranet, etc. Different business users use it for different purposes to make Power BI connect to the data source and generate the required reports.

For our bank itself, there are various tools used by different business users. Some people use MicroStrategy; some use Cognos or its next product. We wanted to have one common tool that any business user can use for analytics. 

Power BI, once made available, can connect to various data sources, irrespective of the application, whether it be HR or business applications. The bank has many applications, but all eventually need to generate reports for tracking, distribution, or problem-finding based on analysis. Power BI was made available as part of the productivity suite to all businesses, which can connect to their applications and provide the reports and analysis they require. 

So, it's more of a strategic tool for the bank to consolidate different siloed business analytic tools with Power BI, serving everyone in the business regardless of what applications they use; they can use Power BI to generate reports.

Power BI also offers mobile app benefits for data access and analysis. The mobile app is available but only in read mode. We are a bank, so there are specific data protection capabilities required to make this available for use on mobile. However, it is already part of the BI suite, and it is easy for us to roll out using Intune. 

Intune is another product we use to manage applications on mobile devices. It can protect data in case someone tries to copy it out. While Power BI has a mobility function, the bank has to ensure that the right protection technology is available. Microsoft Intune integrates very well, allowing us to apply protection policies, but at this point in time, it has not been rolled out.

In Power BI, there are two types of users: power users and light users. For those who don't have heavy use, we allow them to use the web version, which is quite light. They don't need to do much—they can click, and there are templates available that allow them to quickly connect to the data source. 

Even novice users can make use of it, and then they can apply the company-wide protection policies available. For example, we use other Microsoft suites, like Azure Information Protection, etc. So, it integrates well with our Microsoft suite. That's one feature that is quite useful for all users, and their learning curve is very less. It's about the integrated productivity suites.

One of the things Power BI offers is, once connected, it provides tools for cleaning the data, shaping it for analysis, or transforming the data. For example, a user wants to load a comma-separated values (CSV) file and filter some of the data, focusing probably on creating reports based on two columns. It offers on-the-fly filtering capability, allowing them to clean by just removing unnecessary parts and focusing on the areas the user intends to create reports on. 

Then, if they want to perform calculations based on only those two columns or say they want to find all the customers who have contributed revenue of more than two million and have been with us for three years, these kinds of ad hoc reports can be quickly analyzed. This is for a novice user. 

For an advanced user who needs to build relationships between data, that kind of modeling is available; they can take two different data sources, extract, and manipulate relationships between these different Excel sheets or data sources, and then match and append the data. It provides that transformation capability. Other tools also provide this, but because it is well integrated, and for those who are familiar with Microsoft Excel, it feels very familiar.

Some of the features are interactive as well. The dashboards are quite interactive, providing visualization templates quickly. Of course, there are plenty of other tools, but Power BI helps to integrate with our internal productivity tools. People are familiar with it, and it offers all the essential capabilities other tools provide in terms of data cleaning, transformation, or data modeling.

So, comparing Power BI to MicroStrategy, for example, some other tools are quite robust in terms of data analytics. 

From a scalability and performance perspective and based on my understanding and feedback from end users, there's room for improvement in data processing, scaling up, and leveraging the cloud. That could be an enhancement area for me to look into.

I have been working with it for three years. 

I would rate the stability an eight out of ten. It is pretty stable. 

Personally, I use it every week because I need to generate reports for my team. Given the size of our bank, it is being used every day by various departments.

Microsoft is responsive.

Positive

We used different solutions, ranging from Excel to Microstrategy to various other business automation tools.

Power BI became part of our toolkit after we moved to Microsoft Office 365. It fits the requirements of 70% to 80% of the people in the bank, making it a strategic tool. If there are special needs, individuals might choose other tools, but overall, it is available for all users.

So, the bank has an Office 365 contract with Microsoft, which includes various services like SharePoint, Teams, and OneDrive. It is used as a productivity solution in the bank. In doing so, we also need to mitigate risks, such as malicious attachments, links, and files attempting to steal credentials.

Microsoft Defender for Office 365 helps the bank mitigate these risks. It performs real-time scanning and uses machine-learning algorithms to help us detect and block threats. So, we use it as part of our Office 365 to mitigate risk against our productivity suite of applications.

There are three Defender products.

• One is Microsoft Defender for Office 365, also known as MDO.
• The other products under the Defender category are Microsoft Defender for Endpoint and Microsoft Defender for Identity.

So, there are three products: MDO, which is used for Office 365; Microsoft Defender for Endpoint, which is used as an endpoint solution on desktops; and Microsoft Defender for Identity, which is a sensor used in our identity management. The one we mainly use is MDO.

Power BI has good integration capabilities with Microsoft suite products and backend products like SQL and SharePoint, both on-premise and online, as well as other internal applications using databases like SQL or Oracle.

The Power BI on the cloud is very easy. Just turn on the license, but there is some administrative work to be done. 

On a scale from one to ten, rolling out Power BI is probably an eight out of ten, compared to other products, which can be very complicated. However, there's the question of whether it can handle large datasets as well as other tools or provide advanced analytics on par with tools like MicroStrategy. That's what I understand from our end users who deal with huge amounts of data. 

There are areas like statistical modeling or forecasting where other tools might be slightly better. But those use specialized tools compared to Power BI. 

Otherwise, in terms of integration, it's quite easy. Mobility is easy. From an administrative perspective, setting up is very easy because it's just part of Office 365, and we can package and roll it out as a desktop tool as well.

The Power BI license is available on the cloud, so those who have licenses can use it there. It is also available as a desktop client app for those wanting to do more robust reports. It is packaged as part of a desktop product and pushed as a desktop point.

Our business units consume it directly from us at the whole bank level; we make it available. If a department needs specialization, they may get consultants or hire people specialized in Power BI, depending on their requirements. They might put in more effort or recruit manpower to bring in the expertise needed by the bank. 

If a team is already well-versed with business analytics professionals, it's straightforward. However, for a team like us, we might send one or two people for a week's training with Microsoft or another provider. It's not a complicated product for small-scale use. For handling large databases, specialized recruitment may be necessary to manage the workload effectively.

Deployment is very efficient. We have a standard packaging team. As part of the desktop image, when people request, it is pushed through Microsoft SCCM. Packaging takes some time, which is standard across all products. 

When people request, it's automatically pushed. So it's all automated for us. From an end-user perspective, it's very transparent, auto-provisioned on demand.

It's cheap compared to other solutions.

I would recommend using this solution. Within the bank, we mandate the use of Power BI first. If it can't meet specific requirements, then departments might look for other solutions. 

Outside the company, I would say it's value for money, especially for those with a lot of SQL databases or .NET applications. It's a product worth considering for its value.

Positive

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.