Microsoft Power BI Reviews

Microsoft Power BI serves as a visualization tool for our project at Cognizant, primarily used for data visualization and business intelligence reporting. As a data engineer, I use Microsoft Power BI to create many dashboards and reports from the data which we manage through Oracle SQL Developer and SQL Server. Our final target tables are BigQuery and Redshift, from where we fetch the data and then create KPIs to develop dashboards in Microsoft Power BI so that business users can easily analyze the data.

My decision on which KPIs or metrics to visualize in Microsoft Power BI is based on service requests from business users. For example, since ours is a restaurant project, a user might request sales data for a particular site in the USA from the past two months and ask to compare the same data from the previous year to check whether sales increased comparatively so that we can determine what level the restaurant site stands out on an annual profit basis. For such requests, we create a separate KPI. Additionally, for routine tasks, there are already predefined KPIs from which we create the dashboards.

Microsoft Power BI is also used for ad-hoc analysis and sharing interactive dashboards with stakeholders across our organization.

Some of the best features Microsoft Power BI offers are its interactive dashboards and the variety of charts available, such as bar graphs, pie charts, line graphs, and map plots. There are many data visualization capabilities and we can integrate with other multiple data sources very easily. These are some of the main features which I appreciate about Microsoft Power BI. Additionally, we can easily connect to SQL databases or cloud platforms such as GCP, AWS, or Microsoft Azure, as well as Excel. From these different kinds of sources, we can easily integrate into Microsoft Power BI and develop data visualization dashboards.

The feature that I find myself using the most in Microsoft Power BI is DAX, Data Analysis Expressions. It is a separate language in Microsoft Power BI which is very powerful for creating different measures and columns. This is one of the features which I use the most.

Microsoft Power BI creates real-time dashboards and also provides scheduled data refresh so that manual work is eliminated. Once we create the dashboard, it automatically refreshes at a particular time when the data gets loaded and is sent out to the respective business users daily. This is another feature which I appreciate.

Microsoft Power BI significantly improved our organization's reporting capabilities. Previously, we used to report using static reports, but now we have interactive dashboards which allow users to access data in real time. The integration of Microsoft Power BI provides interactive dashboards which are easily understandable to business users because of its different chart options. Decision-making has become faster because stakeholders can access these reports at any time. The data is getting refreshed easily and integration with different sources has made decision-making very faster while reducing the dependency on the manual reporting process and improving data transparency across our teams. Overall, it has enhanced data-driven decision-making and reporting efficiency in our project at Cognizant.

Microsoft Power BI has many features and there is not a lot to improve. However, the licensing can be confusing. When deciding between Pro and Premium, I find it difficult to distinguish what features are offered by Pro and what features are offered by Premium, including the particular differences to choose between both licensing models. Additionally, some features such as DAX, which I mentioned previously, involve DAX calculations and complex data modeling, which are somewhat advanced and not easily understandable. Prior knowledge is required or you need to go through the documentation. If the documentation is made comprehensive so that anyone with no knowledge on DAX can easily use it by going through the documentation, it would be really helpful. Additionally, if the integration with non-Microsoft tools is improved and performance is optimized, then Microsoft Power BI can become a top-ranked visualization tool.

The user experience with Microsoft Power BI is quite good. The intuitive user interface makes it easy for both technical and non-technical users to create reports. However, only the advanced features are somewhat complex, and if the documentation is improved, it can be easily accessible.

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

Microsoft Power BI is stable and reliable, especially the cloud service. We rarely face any downtime or server issues.

Microsoft Power BI is scalable and can handle enterprise-level reporting when using the Premium package.

Microsoft Power BI provides good documentation and community support because of its large user base, along with the Microsoft customer support and enterprise support options.

We have previously used Looker BI.

We have invested a lot in Microsoft Power BI, and the return on investment is quite good. It is saving us around one and a half hours per day on average since we shifted to Microsoft Power BI. Because of integration with Microsoft Power BI, its interactive dashboards, and how easily it integrates with other SQL data sources, business decisions from business users have become much faster because of how easily they can understand the data through the visualizations from Microsoft Power BI. Our project efficiency improved and, on average, one and a half hours have been saved per day because of Microsoft Power BI.

We have evaluated Looker BI, Tableau, and Microsoft Power BI, out of which we have chosen Microsoft Power BI.

I would recommend Microsoft Power BI for individuals or organizations looking for a cost-effective and powerful BI tool. It is suitable for both beginners and experienced users because of its user-friendly nature. To get the best results or to know more about how to use Microsoft Power BI, it is advised to learn DAX and data modeling concepts before using Microsoft Power BI. I would advise going through the documentation so that you get an idea about what Microsoft Power BI is. I would rate this product an eight out of ten.

I use Microsoft Power BI primarily for reserving in insurance, and I have a use case now for expense control, with additional focus on reconciliation.

Some of the best features in Microsoft Power BI include the connection to Anaplan, as I'm an Anaplan developer, and I use that functionality to pull data from Anaplan into Microsoft Power BI.

Deployment for Microsoft Power BI is easier than other tools, making it straightforward, and as an end-user tool, it has been going well since it doesn't require much involvement from a developer team, which releases some time for other development.

The drag-and-drop interface is good, and I notice that the end users manage to produce dashboards very quickly with that feature. I have utilized Microsoft Power BI's natural language processing feature, and overall, my impression from using this feature is that it's good and works well. Collaboration with Microsoft Power BI's other tools helps improve communication in my team.

Regarding drawbacks or weak points in Microsoft Power BI, it may not be directly related to the tool itself, but with our architecture, as we couldn't get a service account, which is an email address that has no relationship with the employees, just to establish the connection with Anaplan. We couldn't get it to work on SSO, so we use an employee account which could be a point of weakness, meaning if the person leaves, that connection will break. If the person goes on holiday and we need to refresh, we have to change the connection as well, but we have to live with that since we're not using SSO on the service account.

Regarding the natural language processing feature, we're trying to avoid using it too much because it can slow down the connection, so as much as possible, we try to build the logic and any transformation in Anaplan, and then deliver an end product to Microsoft Power BI.

I have been working with Microsoft Power BI for approximately one and a half years.

I do not use Microsoft Power BI for real-time data updates, as it is close to real time. We have a group and then we ask the data to be refreshed live in the desktop, but not real time. There is an automated option for that, but we don't use it.

For an initial dashboard for initial testing, we can get it done in a day, but if you allow comments and feedback, it takes much longer than that, which is what really creates the delay.

We have never actually contacted Microsoft for technical support regarding Microsoft Power BI. The only issue we had was the connection with Anaplan, and we tried to engage with Anaplan to overcome that.

Overall, four or five people were involved in this implementation process, including end users and engineers. I would estimate two engineers to end users as a good ratio.

I don't use the drag-and-drop interface much, as it's more the end users who do, while I handle more of the configuration and data preparation to supply the dashboards. My overall experience in IT includes software since starting with Excel and VBA, beginning in 2007 or 2008. I have no knowledge of pricing for Microsoft Power BI, unfortunately; for that, you need to ask procurement. I assess my overall experience with Microsoft Power BI as a rating of nine out of ten.

My main use case for Microsoft Power BI is creating dashboards and visualizing data from reports that we pull from ServiceNow to present to our stakeholders and higher management.

A specific example of a dashboard I have created with Microsoft Power BI is a performance report which includes the performance of each individual contributor in the management. I create dashboards which represent the workload that we usually receive on a monthly, weekly, and daily basis. I also create dashboards that represent sales and purchases that occurred in a quarter or month in the organization.

I have integrated Microsoft Power BI with our different tools including Control-M and ServiceNow. We pull out the details of all job execution and requests that we usually receive, which could be incidents, problem tickets, service tickets, service request tickets, or problem statements from ServiceNow. We integrate that information and then create dashboards on Microsoft Power BI.

In our daily activities, we have Microsoft Power BI integrated with ServiceNow, Rally for defect tickets, BMC Remedy, and Control-M. I would also add that we had integrated Microsoft Power BI with a few of our internal databases to pull out details and create dashboards.

The best features Microsoft Power BI offers are that it is easy to use and easy to create dashboards with a click and drop interface requiring only a few logic inputs in human language. The good part is that it can be integrated with multiple tools.

Microsoft Power BI has positively impacted our organization because it has saved a lot of time in creating dashboards, which we were previously doing in Excel sheets. There were many logic inputs that needed to be added and multiple training sessions that needed to be provided to individual contributors. We are now saving time and have professional dashboards to present to our management and stakeholders.

We are saving around two to three hours per day in creating dashboards with Microsoft Power BI, compared to before when we were utilizing significantly more time to create dashboards via Excel sheets, which were not as professional.

I think Microsoft Power BI can be improved by integrating it with artificial intelligence because AI is new to the market. There could and should be a few dashboards that could be created automatically by simply providing a logic input.

I wish Microsoft Power BI could be integrated with more tools so that it would be easier to pull out the data.

I have been using Microsoft Power BI for the last four years.

Microsoft Power BI is stable.

The scalability of Microsoft Power BI is good, easy to use, convenient, and very scalable.

Customer support for all Microsoft tools is fine.

Before using Microsoft Power BI, we were totally dependent upon Excel to create dashboards.

I had checked Tableau before choosing Microsoft Power BI.

I have seen a return on investment with Microsoft Power BI, including money saved and fewer employees needed.

My experience with pricing, setup cost, and licensing for Microsoft Power BI is that pricing is definitely fine compared to tools like Tableau. It is convenient and easy to use.

My advice to others looking into using Microsoft Power BI is that it is a powerful tool for creating dashboards with very easy handling, a drag and drop option, and a few logic inputs that need to be learned via DAX. Otherwise, it is very convenient to use. I would rate this product a 9 out of 10.

I use Microsoft Power BI to build dashboards and reports for people analytics. This includes headcount, attrition, service delivery, and data quality. All the reports my team and I produce are specifically for the HR or people functions.

I'm very focused on the ETL part of Microsoft Power BI. I particularly enjoy the Power Query functions and functionalities associated with that. In the organizations where I've worked with Microsoft Power BI, we never had an external data source. Most of the time we are working with data exports from various systems. I think Power Query within Microsoft Power BI is one of the more powerful features that I'm using.

The Power Query feature in Microsoft Power BI helps me with the extract, transformation, and load of data. I'm actually doing the majority of the data prep inside that part of the tool.

I appreciate the real-time data processing capabilities in Microsoft Power BI. We don't use them very often, unless we have a real-time data source. With the infrastructure available to me and the team in the organizations I've worked, we didn't manage to have real-time connections to the human capital management tools. One of the use cases I had was when we were collecting feedback from new joiners. It was a real-time data update because we connected Microsoft Forms, which was the source of data, to a real-time dashboard that we created in Microsoft Power BI. Each time someone submitted new feedback for their onboarding survey, the data would flow automatically without requiring manual intervention. This isn't the typical situation. More integrations for human capital management tools would be great, though it depends significantly on the organization.

Microsoft Power BI can be quite slow when working with data sources that aren't from a data warehouse or a more robust source or data artifact. When working with exports, which we do frequently, the load takes considerable time. This occurs with any BI tool, and it's related to our working methods due to limitations within the area. In HR, we typically use exports because we have numerous data sources.

Ideally, Microsoft Power BI would have a no-code or low-code solution for the data sources to be built by the actual developers or development team. This would eliminate the need to work directly with exports. We would have a middle ground to create a warehouse without all the infrastructure, as building a warehouse within an organization can require substantial resources, both in time and personnel.

I have been working with Microsoft Power BI since 2019.

It has been performing consistently throughout all these years.

Scalability depends significantly on how the report is being set up in Microsoft Power BI. If we had a large number of users, such as hundreds of users for different reports, we would need to have a conversation with tech support to build access groups in Azure.

I am part of a very complex organization, but in my area within the people function, there are just under 100 people working with Microsoft Power BI.

In one of my previous jobs, we contacted Microsoft support, though I struggle to remember the specific reason.

Neutral

For the exact same purpose, I haven't used other solutions, but I have tried working with Tableau. I also have some experience working with Click Sense, though this was only after working with Microsoft Power BI.

It is very easy to set up Microsoft Power BI, and I have become very accustomed to it over many years.

The implementation process doesn't require much effort. It involves requesting tech support to allow the installation of Microsoft Power BI, approving the installation, and providing licenses to each team member. The entire process takes one day maximum.

From my perspective, Microsoft Power BI works quite easily. I have also worked with Tableau, which is considerably more difficult. For example, we recently encountered issues while trying to migrate our Microsoft Power BI reports into Tableau. With Tableau, it's very difficult to work with sources stored on SharePoint, though this might be an organizational limitation. Microsoft Power BI works more seamlessly with SharePoint because it's the same Microsoft environment.

We're using the organizational setup for Microsoft Power BI. We use Microsoft Power BI service online, but it's just the organizational service. We never use anything to publish reports publicly.

I am aware of Copilot in Microsoft Power BI, though it's disabled for us and I haven't explored it extensively.

Microsoft Power BI is pretty self-explanatory and becomes more complex as you try to solve challenges and business requests. Most of the time, there is a workaround available. There are many resources available to help you get started, and you don't necessarily need to invest heavily in courses or certifications.

I rate Microsoft Power BI 10 out of 10.

There are so many use cases of Microsoft Power BI. For example, the first use case is in manufacturing automation, where clients in the ready-mix concrete sector are using it. We collect and analyze user and operator feedback to optimize operational performance in manufacturing while also taking data from their sales projections.

Role-wise, it is being created, and function-wise, we look at sales data from last year and the last quarter versus the current quarter to identify gaps and required run rates to meet sales goals. Microsoft Power BI predicts whether they will reach the previous year's sales and their desired target for this year based on current run rates, showing the optimized revenue needed per day to achieve their goals.

My customers are in other industries beyond manufacturing with Microsoft Power BI.

Currently, we are working with the finance sector; it's a non-banking financial company (NBFC) client, not a bank.

The demand estimation and forecasting profitability are the most effective features of Microsoft Power BI, along with vendor and supply chain risk analysis, inventory and stock forecasting, real-time production monitoring, and quality control through defect tracking and root cause analysis.

Most clients using Microsoft Power BI are also using ERP systems, so we pull data from their operational databases rather than Excel or Google Sheets; the data is synced in real-time or within a 7 to 15-day window based on client needs.

Microsoft Power BI is easy to integrate with other solutions; regarding AI, it supports machine learning projects for customers.

The challenges our customers face with Microsoft Power BI are more about how we're implementing it; every customer's business workflow is unique, which means that the framework needs to be customized according to their specific requirements.

I haven't thought about improvements for Microsoft Power BI as of now, but one area I can suggest focuses on the need for strong native data cleaning or data quality validation functions since Microsoft Power BI assumes the data is pre-cleaned.

Setting up Microsoft Power BI is not very easy, yet DAX is powerful; from the interface perspective, I have no feedback, as it's acceptable.

I have been working with Microsoft Power BI for the last seven months.

The deployment time for Microsoft Power BI depends on how quickly we understand the client's business logic and usually takes from one to two weeks for discovery planning, another two to three weeks for data preparation and modeling, about four to five months for design and development, plus two to three weeks for deployment and integration, and an additional two weeks for training and optimization, totaling from two to four months ideally.

Microsoft Power BI is stable; however, the data refresh frequency of eight times daily may not meet the needs for businesses requiring real-time or very frequent updates.

The issue with the data refresh frequency in Microsoft Power BI is that it's not frequent enough.

Microsoft Power BI is easy to scale.

Support for Microsoft Power BI is good; our implementer manages everything, and I haven't faced any issues from Microsoft so far, as there are self-help resources and community support available.

Positive

I would rate the setup of Microsoft Power BI as a nine.

I have a dedicated development team working with Microsoft Power BI, so we are in customer service.

We are a service provider implementing Microsoft Power BI for our customers, customizing their business workflows according to the Microsoft Power BI framework and the dashboards they want, which may involve finance, sales, or manufacturing metrics.

The cost of Microsoft Power BI is competitive; currently, the Pro version is around $14 per month per user, which is a 40% increase from previously $10, and the Premium version is $24 per user per month, a 20% increase from the prior $20.

I create data analytic tools for clients using the Microsoft Power BI framework. I always recommend using Microsoft Power BI, as it will significantly increase business. On a scale of 1-10, I rate Microsoft Power BI a 9.

I am currently a tech lead in data science for the Middle East team at Vodafone, especially working with Cloudera CDP cluster. I administer three mega clusters: one for production, one for disaster recovery, and one for AI and machine learning practice. I cover the administration part and how to build the cluster from the beginning. In the development cycle, I have successfully integrated different tools into Cloudera such as Microsoft Power BI. I fully integrated this visualization tool, so now we can report the data directly from Data Lake. This is the modern approach because the market leads to having one single source of truth. We apply the Medallion Architecture and report directly to business users from the Data Lake without needing the middle layer such as a data warehouse.

I have five years of experience working with Microsoft Power BI. I have already developed over twenty dashboards for the commercial and finance teams, with different types of dashboards. I cannot share the actual dashboards because this is confidential information, but I can show you how I simulate the data and gather meaningful insights that help businesses make decisions quickly. I also developed dashboards for a mega transportation company in KSA called Welcome or Arheb. Currently, I am developing my experience to lead other teams on how to develop the best scenarios in Microsoft Power BI.

Microsoft Power BI is a powerful tool with many capabilities, but my favorite feature is its data modeling. It has many capabilities to link tables together and determine what you need specifically to get insights for KPIs. The same dashboard can serve different teams who have experience in how to model the data differently to fulfill the requirements. Additionally, Power Query can handle basic ETL and data cleaning, but I do not favor this approach because Microsoft Power BI is the end layer. I handle the ETL and development outside Microsoft Power BI and then choose the right approach for the dashboard, whether it needs to be real-time or patched. I can choose direct query, import mode, and reschedule the dashboard to refresh weekly, daily, or even hourly. All of these capabilities are present in Microsoft Power BI and more.

The drag and drop interface in Microsoft Power BI is straightforward. It allows you to drag and drop visuals and create meaningful insights. However, the deep concept is how to create meaningful insights because it is not just about having a powerful chart or visuals. I am focused on the significance of the data. The drag and drop visualization in Microsoft Power BI is straightforward, but initially, I focus on data modeling, validation, and quality. I ensure all of this is good before moving forward to visualization.

Inside Microsoft Power BI, I generate Row-Level Security (RLS) and share the dashboards in one source on the cloud or a shared link. I track changes via version control such as Git, and collaborate together. Everyone has a development plan, any changes or enhancements are aligned with us. I determine downtime for applying these changes successfully and accurately. If I face any issues, I can roll back to the old version, and everything runs smoothly.

I believe the enhancement in Microsoft Power BI should focus on cleaning or validating the data. Bad performance or heavy load on the dashboard often results from issues in backend data modeling or invalid data. Ensuring quality queries and equations makes the dashboard run smoothly every time. I am totally focused on not just delivering data but delivering quality data, checking the validation of each process in data.

I have been working in my current field for seven years.

I have not experienced significant stability or performance issues with Microsoft Power BI. I have faced some issues similar to any software tool, but they can be handled with workarounds and experience.

Cloudera especially needs our infrastructure. It is straightforward; I can integrate it with any cloud provider, including AWS, Azure, and GCP. All of this is straightforward.

I did not work with Microsoft Power BI's natural language processing. However, I believe it is straightforward to implement a Python script embedded in Microsoft Power BI, which can handle how to generate dynamic visuals through NLP. I already implemented an in-house LLM model at Vodafone that helps developers check SQL queries from the data warehouse and automatically generate reports by gathering information from the end user. I developed this project end-to-end, and it is in my CV. It covers manual handling from developers, and I believe I can implement the same inside Microsoft Power BI.

Neutral

I have worked with many other BI solutions such as Looker, Tableau, and Data Fabric end-to-end. The concept is the same across tools; if you master one tool, you can handle others with similar concepts.

Microsoft Power BI and other BI products such as Tableau and Looker are similar, but Microsoft Power BI is more powerful and has more capabilities, especially since it has a free version. Many people cannot work or simulate dashboards in Tableau without a corporate license, while Microsoft Power BI allows that. Looker, supported by Google, is similar. I find that there are no significant pros and cons, but rather it depends on how familiar one becomes with each tool.

The initial setup of Microsoft Power BI depends on the volume of data being dealt with, whether it is natural data or big data. Different approaches apply based on the type of data, such as handling a distributed system or a specific platform.

I already utilize real-time data updates in Microsoft Power BI using a feature called DirectQuery. DirectQuery hits the database in real-time and gathers updated data every time the dashboard is refreshed.

Microsoft Power BI has the capability to integrate with different systems such as Cloudera, Impala, Hive, and any Apache technologies. In the new versions, Microsoft Power BI added new technologies to enhance integration, making it an embedded feature. I do not have any fees associated with Microsoft Power BI. My overall review rating for Microsoft Power BI is nine out of ten.

In terms of my relationship with Microsoft Power BI, I am a user. For deployment in my organization, I don't know the details because I'm an end-user.

One of the most valuable features of Microsoft Power BI is process mapping, although I don't know the exact name by heart.

I have seen some measurable benefits from Microsoft Power BI. I cannot quantify it, but it's definitely time-saving. There are non-tangible benefits such as its superior design compared to Qlik.

Regarding the data integration capabilities of Microsoft Power BI, I have no issues with these but I feel they can be faster, better, and more intuitive. It's generally acceptable.

Microsoft Power BI is integrated into SharePoint, which is very good, but I don't think there can be much improvement done. It's dynamic, and I'm satisfied with this aspect.

Regarding real-time analytics features in Microsoft Power BI, I don't find them particularly useful. I use process mapping, but from my point of view, there are not enough analytical tools.

My experience with Microsoft Power BI spans approximately two to three years.

The initial setup of Microsoft Power BI was easy and not problematic.

Microsoft Power BI is a stable solution, and there are no issues with stability.

The scalability of Microsoft Power BI is good, and because we use it embedded in PowerPoint as I think it is scalable.

I would rate my experience with technical support of Microsoft Power BI as zero because I haven't had the opportunity to contact technical support. Whatever I accomplished, I did myself or through reading instructions on the internet. Technical support is not available to me.

Before Microsoft Power BI, we used Qlik and Cognos. When comparing these solutions, Microsoft Power BI is significantly better.

The initial setup of Microsoft Power BI was easy and not problematic.

The deployment of Microsoft Power BI was definitely done in-house by our organization.

I have seen some measurable benefits from Microsoft Power BI. While I cannot quantify it precisely, it is definitely time-saving. There are non-tangible benefits such as its superior design compared to Qlik.

Before Microsoft Power BI, we used Qlik and Cognos. When comparing these solutions, Microsoft Power BI is significantly better.

In my organization's small branch, approximately 10 people use Microsoft Power BI, but I don't know the total number across the organization.

I haven't used Microsoft Power BI for AI-driven projects, but we are planning to incorporate it with machine learning and AI now.

I don't have specific advice for people considering Microsoft Power BI because every organization has different needs and expectations.

On a scale of 1-10, I rate Microsoft Power BI a 10.

I primarily use Power BI for data visualization. I build dashboards on Power BI, which are then distributed to a larger audience for day-to-day operations, like data management and similar tasks. 

In some cases, I have used Power BI to manage very large data sets, which isn't possible with Excel, Access, or other tools. I created custom solutions on Power BI that allow users to cut and slice through the data we have. These are the two main use cases I've observed so far.

One of the key factors why I use Power BI is because it's very flexible with other Microsoft tools. The entire ETL process is easy and supports many databases, allowing data pipelines from multiple sources to be gathered in one place for visualization. This is the key aspect I like about it.

Real-time data integration is an area for improvement. Although I've worked on several solutions involving real-time integration, it's not very user-friendly and often lags, especially with over a million data rows. This makes Power BI difficult to manage as loading times can reach one or two minutes, which is problematic today. 

There are challenges with scalability, requiring multiple pages in dashboards to manage these issues. Visualization could be improved as it appears outdated. Users, especially newcomers, find it unappealing and not user-friendly.

I have used it for almost five to six years.

It's stable, with no significant issues. In terms of stability, there's no data loss or leakage, and precautions are well-managed by Microsoft. If data is stored in Power BI, it's secure from corruption. However, while loading data, I've seen it crash multiple times requiring restarts. Such issues surface occasionally.

It's not great in terms of scalability. There are better scalable products available. I've worked in two segments: one with a company with 200 employees where dashboards were internal, and another in a consulting firm with larger-scale templates for up to 4,000 users. You expect only a small percentage of users concurrently, but beyond a thousand concurrent users, it becomes difficult to manage.

Customer service is good, and I'd rate it above eight, specifically eight point five out of ten.

Positive

It depends on the person regarding the learning curve. The UI presents challenges, requiring one or two sessions to guide users through functionalities. There is a learning curve. For developers, Power BI is easier due to available user features in Microsoft suite, but end users find it challenging.

The ROI is high for small teams or basic use cases with limited datasets. Power BI is easy to deploy within an hour, providing robust security against data leaks. However, as data complexity and user capacity increase, moving to other solutions may be beneficial. For small use cases, Power BI offers significant ROI.

We bought it as a package deal with other Microsoft suite features and deployed it on Azure. Power BI isn't very cheap, however, it is economical compared to other solutions available.

I have not seen Power BI associated with machine learning or data science. It is a clear-cut data visualization tool without overlaps in AI. 

The overall product rating is six out of ten.

Power BI is our development visualization system for general analytics and data reporting. I position it on top of our data warehouse, SharePoint data, Excel data, or any available data. It is used for internal purposes, allowing network-wide access from physicians to nurses to operational leaders. We have upwards of 16,000 users.

Power BI is a general-use visualization system. I can express the performance of our network through high-level key performance indicators. It allows me to show detailed improvements in quality and safety and patient experience. I create improvement dashboards for task forces and work teams. I have built analytic dashboards that guide analytics, enabling research and dataset manipulation.

Microsoft updates Power BI monthly based on user community feedback, investing significantly in research and development. They are integrating it into their workspace with Microsoft Fabric and other tools to ensure seamless integration with Excel and their suite of tools.

I have been using it for about eight years here.

Since it is Microsoft, we have a team acting as our gatekeeper for all support services. We typically do not have problems with end-user tools like Excel and Power BI. These tools tend to work smoothly, so there is little need to engage customer service.

Visualization systems are still relatively young. With increasing AI capabilities, architectural developments within Microsoft, and tools like Fabric, I expect Power BI to scale accordingly. Although it is new, it performs well, and it is doing a good job. It is not leading the charge on scalability, but it meets expectations.

For those, I would give them a nine. We have a partnership with Microsoft, involving multiple weekly calls with dedicated personnel to ensure our satisfaction.

Positive

We used QlikView before switching to Microsoft. We believed this change would yield a more scalable and integrated solution. We consolidated our tools, converted everything to the new system, and cancelled our agreement with QlikView.

The initial setup is very straightforward. It does not take long to deploy.

Anyone can download it from the Internet and start using a shareware version, building on datasets independently. We have pro licenses for some developers who perform analytics, BI engineering, and development tasks.

QlikView is a niche system that fulfills its purpose but lacks Microsoft's resources in research and development. It was not a bad system, however, Microsoft's solution was perceived to be more advantageous and suitable for our long-term goals.

The system can be used by individual users and scales for small to large companies. I would give it a nine out of ten. 

Microsoft offers a generative AI solution called Copilot. They are integrating it, although it is still developing. OpenAI is also integrated, but its capabilities are still emerging.

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.