Microsoft Power BI Reviews

There are multiple workflows used in SharePoint and Salesforce. In ServiceNow, workflows are generated for each of the corporate functions such as HR, finance, ORM and others.

Microsoft Power BI is used extensively throughout the organization.

We are seeking agentic AI or analyzing AI which can help automatically analyze requirements and create workflows. Currently, we are creating these manually and must be involved in end-to-end testing. This involves two major parameters. To reduce the need for highly skilled personnel, we can engage someone who is just familiar and has a basic understanding of Microsoft Power BI, while AI can handle the major tasks through either agent AI or requirement analysis.

For example, as a lead, I can produce requirements that can be fed to the AI, which can then generate the workflow. It may also recommend how testing should be conducted, and test cases can be automatically generated by the agentic AI.

I have been using the solution for a couple of years. I serve as a lead for assessing tools, and whatever tool is being assessed is given to our team to use in their daily work.

This is a separate solution which we have implemented for some of our use cases that require the partition approach. On-demand basis operations can be performed without subscribing to the entire platform. We have subscribed to specific features of the platform and are paying for only those features.

The system operates in real-time.

We have not experienced any scalability issues. They are quite supportive with an online community and service desk available. If someone encounters any problems, we utilize these resources.

They are quite supportive with an online community and service desk available. If someone encounters any problems, we utilize these resources.

Positive

We previously used a different solution called UForge.

The initial setup was completed with this German product.

The organization maintains a platinum partnership which provides certain discounts and other benefits from this partnership.

The return on investment rating is eight out of ten.

There are associated setup costs.

There are multiple alternative solutions, particularly in SharePoint and Salesforce.

This is a separate solution which we have implemented for some of our use cases that require the partition approach. On-demand basis operations can be performed without subscribing to the entire platform. We have subscribed to specific features of the platform and are paying for only those features.

We are a platinum partner with Microsoft, so the tools automatically become part of our ecosystem. This follows the usual process of Microsoft.

On a scale of 1-10, I rate this solution an 8.

Microsoft Azure

My use case is not extensive because I am using a module of Eightfold. As a financial controller, I am not directly involved in recruitment myself. I have only seen it on someone else's screen, so I am not a good judge of the solution.

The main feature I find valuable is the possibility to work with an extensive amount of data. While you can achieve some of this with Excel, it takes much longer to perform calculations. 

Power BI processes data differently, efficiently utilizing memory for detailed-level processing. The visual capabilities are another significant advantage over Excel, though Excel continues to improve. Access, however, does not compare in terms of graphical evolutions like those in Qlik. 

Furthermore, the potential to use custom add-ons in Power BI is restricted if you do not use native Microsoft products, which is understandable for quality control. Ultimately, the ability to handle large volumes of data and provide dynamic selections is a considerable benefit. In today's data-driven environment, these tools are of substantial value, particularly for large enterprises with numerous processes that require extensive data analysis.

Sometimes in Power BI, the logic can be challenging to follow. For example, Access worked well by differentiating between the data and the processes applied to the data, which were clearly separate stages. In many applications, including Excel, you finalize the layout with ease. 

With Qlik, though, you are often required to first manipulate data tables before assessing how they look in the report, which might feel counterintuitive to someone accustomed to Access's approach. Access was more logical in how it distinguished between data and its formatting. 

Despite this dual-check process feeling odd, once familiar with it, you adapt. I believe maintaining a clearer distinction, like Access, between data handling and formatting would benefit those new to Power BI.

I have been using the solution for about one year, however, not on a daily basis. I started working with a few layouts last year and recently have worked on another layout. I would consider myself a beginner.

I would rate the stability as a seven out of ten. It's not a bad grade, as I know of better products in this field. However, if starting from nothing, I believe most people would rate it higher.

The significant drawback I notice is that Microsoft's size makes it hard to get specific change requests addressed unless they involve a bug. With smaller suppliers, it's easier to request changes. 

Unfortunately, with Microsoft, you must accept the product as it is. I presume there exists a structured first line of support, but I have not used it, so I cannot comment further.

Neutral

The initial setup is not very easy. Understanding the logic of how to work with that solution takes some time. Unlike Excel, which immediately provides results for input formulas, Power BI requires using DAX code for simple operations, which can be restrictive. 

Certain basic tasks, like bolding a column in the middle of a table, are not possible. While it has many impressive capabilities, Excel feels more open and flexible. Excel seldom leaves you with the sense that a function cannot be done. Power BI, however, can feel more limited in that regard.

There is a substantial benefit to using Power BI. In a world surrounded by data, tools that allow navigation of large data volumes ensure decisions are data-driven. Investing in such tools has a high value, especially for large companies with numerous processes and data demands. Power BI is strategically essential for analyzing large data sets.

I must note that Power BI is not as powerful as Qlik, which is a comparable solution offering superior dynamic data selection. Qlik’s filters are more efficient, especially if detailed data filtering is crucial. 

Power BI's filters are basic in comparison, and the advanced filters can feel awkward. Therefore, if extensive filtering is needed, I believe Qlik is a better choice.

Overall, I would rate the solution as an eight out of ten. 

While Excel has become increasingly capable, making significant improvements, Power BI offers advantages for certain users. Medium-sized companies might find Excel sufficient and of good value. Excel’s evolution with functions like XLOOKUP over VLOOKUP offers ease of use. 

Additionally, tools like Copilot bring another dimension of capabilities. Although Excel is not free, it remains a versatile tool. Some achieve excellent dashboard results with it, comparable to Power BI.

Public Cloud

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.

Public Cloud

The primary use case for Microsoft Power BI is mainly for operational reports. I primarily use it for these types of reports.

The most valuable feature of Microsoft Power BI is the user experience. Additionally, the features that Power BI provides in the cloud present a strong value proposition for me.

I face performance issues with Microsoft Power BI, which are unsolvable. There is a lack of features between the on-premises and cloud version, which poses a challenge for me. Real-time capabilities are also limited, especially on the on-premises version.

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

The stability of Microsoft Power BI depends on the data size. It is very stable for small data, but with big data, there are performance challenges. For example, calling a report with one hundred thousand rows leads to performance issues, necessitating memory injection, which is a long process.

I would rate the scalability with Microsoft Azure as a ten.

I think the support is good because there is also a community available. If any issue arises with Microsoft Power BI, it is easy for me to find a solution. I would rate it a ten.

Positive

The initial setup process is very simple.

The pricing for Microsoft Power BI is low, which is a good selling point.

The only limitation is the customer size. For smaller to medium-sized clients, I recommend Microsoft Power BI. However, for enterprise-level clients, it is better to recommend non-Microsoft Power BI technology due to the need for robust support as a system integrator. Overall, I would rate Microsoft Power BI an eight.

On-premises

Microsoft Azure

We use it specifically for pure data analysis. 

I like the speed of building a visual and the transformation feature where you can make changes to the data, and then revert back very fast. These features, where you make transformations and then delete that step when you don't need them, are some of the best.

Power BI's integration with other tools is very good. With Power BI, if there are other systems on the network, you can easily connect to anything like SQL Server, Oracle, Amazon, Salesforce, SAP...anything you can easily connect. I have not faced difficulties with that.

The real-time data refresh capabilities is one of the things I had issues with. The refresh sometimes doesn't really work very well because there are two ways of connecting: direct and import. 

When it's direct, it's refreshed, but then you have limitations. But when you import the data, I feel there is always a limitation in the refresh. It is kind of like a room for improvement for Microsoft Power BI to work more on these real-time data refresh capabilities.

Microsoft Power BI changes almost every month; make changes regularly. I sometimes even see features that disappear, change, and update. So, I'm not keeping up. They are already doing a lot of changes. They keep updating regularly.

I have been using it for six to seven years. 

It's quite stable. Power BI is very stable.

It is very scalable. Almost everyone in our company uses it. 

I personally use it daily. 

I don't usually deal with customer service and support. It's our technical team that deals with them, but I don't see them complaining.

I used Excel. Power BI can crunch the data faster, and you can build a dashboard nicer and faster. Building a visual in Power BI is always easier, quicker, and simpler than Excel. It's Excel on steroids. 

I used to use Excel pivot tables a lot, but with Power BI, it's faster. It's easier to play with the data. If I want to make a list or put some formulas and stuff, Excel is good. But if I want to visualize the data, crunch it properly, and build measures quickly, Power BI is better.

I would rate my experience with the initial setup an eight out of ten, with ten being easy and one being very difficult. 

It is deployed both on-premises and the cloud. 

The deployment time varies and depends on the company. Every company is different. Here, internally, we have Microsoft Power BI Cloud, so it's easy. 

But in the previous company, we did not have Microsoft Cloud. So, to install, we had to install Microsoft Reporting Server and then Power BI internally. That took quite a while. 

But if you have Microsoft Cloud in your company, that's easy. And it's quicker on the cloud than on-premises.

Maybe a third party helped with the deployment. 

Downloading Power BI Desktop is free. But when you want to use the cloud, this is where I think it's per user payment. I'm not really very familiar with the licensing because I think they have more than one level. 

But to use Power BI internally for yourself, it's free. You download it. It's a free application.

I would recommend Power BI to other people. Overall, I would rate it an eight out of ten. 

In my company, we use Microsoft Power BI only for monitoring because now it is the only software you can use to connect to Azure DevOps. We use the tool to monitor our environment, activities, and KPIs and evaluate bug rates and future values. In our company, we use agile scrum methodology, and for every activity that we create in our backlog, we monitor the life of the activity in our backlog. When we deliver the above-mentioned features, we use the Microsoft Power BI to monitor and create KPIs.

The dashboard is very nice and it is very simple to understand every single component. You would use a new task manager to monitor goals to manage your team, but I don't like that and would prefer to work with and learn a new tool that does monitoring. Sometimes, we use Azure to measure every dashboard and to monitor the activity in the scrum, but only under the dashboard. For example, more or less the two or three KPIs can be monitored using your monitoring tool.

In our company, we don't have any big problems with the tool because I have only one member from the main team who works on Microsoft Power BI to create, or sometimes, when we push the request to bring a new dashboard in the tool. I currently have two members working on the same dashboard, but only one member can work on the dashboard at a time. Whenever you work on the same dashboard or on the same code, Microsoft Power BI doesn't have a good architecture that allows multiple people to work on the same project.

I have been using Microsoft Power BI for a year.

It is a stable solution. The tool is static after you create the language and put it inside the dashboard. You can schedule the report at a particular time in the day, making it a very simple tool with a scheduler to run your reports. I think it is a stable tool, but we don't stress a lot on our infrastructure with Microsoft Power BI. Stability-wise, I rate the solution a ten out of ten.

For me, scalability is hard to learn. I don't think it is a good tool for which the scalability part should be evaluated.

Scalability-wise, I rate the solution a five out of ten.

The technical support for the solution is very fast, but finding the right technical person is not easy. I rate the technical support an eight out of ten.

Positive

The problem with Microsoft Power BI is that we can use any language or developer language. Now, we have a small problem when different members of my team work on the same project on the same dashboard. We now connect Microsoft Power BI to Git, and we deliver it, but, of course, the tool is not engineered to function in such a manner. We face issues when lots of members work together.

The solution is deployed on a private cloud model, but I don't know what infrastructure is needed to use it. Five months ago, my company switched from the tool's on-premises version to the cloud one.

I find Microsoft Power BI to be the most effective for data integration.

Microsoft Power BI actually dramatically improved our company's data visualization, and if we are lucky, then we have the features inside of the tool itself, which we can develop, and it is a very fast process. When you need a new feature or a new dashboard, and when we don't have any good news on the internet from Microsoft, we need to develop such features from scratch, for which we spend a lot of time creating a new dashboard for monitoring purposes.

Microsoft Power BI impacted our operational costs, and the benefits are nice because you can monitor everything. The advantage that we have in Microsoft Power BI is something we need to learn, especially the new language and new tool, but it is not our focus because I am the leader of the software engineering team. Microsoft Power BI Power is a tool to support my team, and my first activity involved managing tasks.

Microsoft Power BI has handled scalability as our company's data analytics needs have grown because you can use the tool's scalability feature on the cloud. If I need to add a new member to work on Microsoft Power BI, I don't think it is good because every single person can work on a single dashboard offered by the tool, but if you would scale up, then you won't be able to work using one dashboard.

Though I have no idea how the maintenance is done, I know that it is a process carried out by our company's team members.

I rate the tool a five out of ten.

Private Cloud

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.

I use Microsoft Power BI a lot for visuals in my work.

The most valuable feature of Microsoft Power BI is the drill-through feature that takes you to a details page the users want to see. The solution helped with the visuals, and it is easier to use compared to other things that we used before.

When we have a big report with lots of data, the solution slows down quite a lot. It's not very fast to upload and refresh the real-time data that we use. The solution works fine for a dashboard that does not have much data, many levels, and breakdowns for different fields.

When we build something a bit more complex, Microsoft Power BI takes a lot of time to upload. I don't know if that's the solution's fault or our system's.

Sometimes, the solution doesn't work. You need to have a license, but we integrate it and make it part of our system so everyone can use it without a license. If I share a report in PowerPoint, it takes a while when you deploy it again. So, it's not always fast, and then I have to ask IT for help.

When you export a file, it should be the export that you choose on a report rather than just the raw data. At the moment, it just gives you everything as raw data in a page without any filters.

I only did some courses last year and learned how to use the solution.

After building a report, when you review it, it doesn't have the correct data. Some things don't rebuild after a while, but I don't know if it's our data or the solution's fault.

I rate the solution a seven or eight out of ten for stability.

Microsoft Power BI could be more scalable.

I rate the solution a seven out of ten for scalability.

I previously used Dundas. Compared to Dundas, the visuals look better in Microsoft Power BI. Microsoft Power BI gives you the option to have paginated reports rather than just one page, which I find quite easy.

On a scale from one to ten, where one is difficult and ten is easy, I rate the solution's initial setup an eight out of ten.

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