Microsoft Power BI Reviews

I use Microsoft Power BI as a customer and within the organization to create dashboards and insights into data. I also build dashboards and use Microsoft Power BI to analyze data.

One of the most valuable features of Microsoft Power BI is its easy way of sharing data within the organization or outside. Users can publish dashboards easily. Additionally, within the organization, Microsoft Power BI is used to create dashboards and gain insights into data, enhancing data-driven decision-making.

One area where Microsoft Power BI could improve is the handling of date calculations. It takes effort to organize dates in graphs in the correct order, often requiring programming conversions or manipulations. Performance can be an issue when there's too much data, and getting data into Microsoft Power BI via APIs can be slow. This may be due to the technology used to import the data. Enhancing performance and data uploading, especially with APIs, would be beneficial.

I have been working with Microsoft Power BI for four or five years.

I'm not sure about the technical setup time as another department handled it. However, the rollout took a couple of months, and it took close to a year to make the functionality fully available to everyone.

On average, Microsoft Power BI is quite stable, though there are occasional hiccups related to performance or issues which might be due to other factors like network or user errors.

Microsoft Power BI scores around six out of ten for scalability. As more data is processed, performance issues may arise.

I haven't interacted much with technical support, but it seems okay, around a six or seven. There's a lot of available knowledge and training on Microsoft Power BI.

Before Microsoft Power BI, we used Splunk to create similar dashboards. Many switched to Microsoft Power BI as it was easier to learn and publish. Splunk is more log-based, whereas Microsoft Power BI is more generic. We also used Excel previously.

The initial setup was not complicated for me. However, the dual nature of the desktop and online versions can be confusing, leading to uncertainty about where certain tasks should be performed.

I recommend Microsoft Power BI to others. I rate the solution overall around a seven as it accomplishes its tasks most of the time. However, performance issues or lack of certain features can arise in certain cases. I would rate the overall solution a seven out of ten.

Public Cloud

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.

Public Cloud

Microsoft Azure

Microsoft Power BI is a business intelligence tool, and we take the data which was preprocessed, refined, cleaned, transformed, and loaded so that it can be used by Microsoft Power BI to get insights from it.

We represent the data using various visualizations such as bar charts and diagrams. By utilizing these functionalities, we gain better insights about the data. It also provides connectivity through various data sources such as SSIS, SSAS, Azure SQL, Synapse Analytics, and Data Lake, allowing Microsoft Power BI to be used efficiently. Additionally, it plays a major role in ETL tasks as well.

The interactive elements in Microsoft Power BI enable us to perform drill-up, drill-down operations, and drill-throughs, and the various types of visualizations, including charts, graphs, maps, matrices, tables, and slices, make it highly adaptable for different case scenarios. The measures help us carry out aggregations and calculations to provide the necessary business insights, such as representing total sales or tracking growth year by year.

For business use cases, real-time data from Microsoft Power BI could be very impactful. With AI in Microsoft Power BI, when we ingest the data and use the GenAI tools at our disposal, AI helps automate the process and represent the visualizations to our customers and clients. For instance, if we want to analyze the growth pattern in the last quarter, the tools can assess the visualization presented and provide us with specific responses.

The interactive elements in Microsoft Power BI enable us to perform drill-up, drill-down operations, and drill-throughs, and the various types of visualizations, including charts, graphs, maps, matrices, tables, and slices, make it highly adaptable for different case scenarios.

The measures help us carry out aggregations and calculations to provide the necessary business insights, such as representing total sales or tracking growth year by year.

With AI in Microsoft Power BI, when we ingest the data and use the GenAI tools at our disposal, AI helps automate the process and represent the visualizations to our customers and clients. For instance, if we want to analyze the growth pattern in the last quarter, the tools can assess the visualization presented and provide us with specific responses.

The low-code, no-code feature in Microsoft Power BI is quite beneficial for business analysts and related associates to work better with it and create meaningful and valuable insights.

The low-code, no-code feature in Microsoft Power BI could be enhanced for business analysts and related associates to work better with it and create meaningful and valuable insights.

If changes are made in the data lake or Synapse and analytics, a useful feature would be for Microsoft Power BI to sense these updates and apply them automatically.

I have been working with Microsoft Power BI for around one year.

I haven't faced any issues while working with Microsoft Power BI. Every time I log into Microsoft Power BI, it works seamlessly without crashes or performance issues, providing a good overall experience.

I haven't faced any issues while working with Microsoft Power BI. Every time I log into Microsoft Power BI, it works seamlessly without crashes or performance issues, providing a good overall experience.

Reaching out to technical support regarding Microsoft Power BI is very rare; mostly, our work can be carried out efficiently without needing assistance. I would rate Microsoft technical support an eight on a scale of one to ten.

Positive

The initial setup of Microsoft Power BI was managed by another team that set up the VDI, so I didn't encounter challenges during its introduction.

The initial setup of Microsoft Power BI was managed by another team that set up the VDI, so I didn't encounter challenges during its introduction.

The pricing of Microsoft Power BI is affordable compared to Tableau, making it accessible, especially with a wide Microsoft community and strong enterprise support.

I have an understanding of Tableau in addition to Microsoft Power BI. Some UI features highlight the differences between Microsoft Power BI and Tableau. The pricing of Microsoft Power BI is affordable compared to Tableau, making it accessible, especially with a wide Microsoft community and strong enterprise support.

I am currently working in the field of data engineering, utilizing tools such as PySpark, PySpark SQL, Python, integration services through SQL Server, and analytical services.

Since the work has been done on migration, I also possess knowledge about AWS and Azure.

I work with Python and have experience with both PyCharm and Visual Studio IDEs.

Reaching out to technical support regarding Microsoft Power BI is very rare as most of our work can be carried out efficiently without needing assistance.

Based on my experience, I would rate Microsoft Power BI a 9 out of 10.

Public Cloud

Microsoft Azure

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

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

I use Microsoft Power BI for data visualization and IT studies. It is used primarily in my academic studies and courses, particularly in my visualization course, which is part of a master's program for individuals currently working in the industry. Students also use similar programs like Excel to monitor various issues.

Using Microsoft Power BI has significantly helped in analyzing large datasets. The solution allows for visualizing and connecting different Microsoft applications, which is beneficial for academic purposes.

The best features of Microsoft Power BI include its integration with other Microsoft products and its ability to connect applications within the Microsoft ecosystem. The product's overall integration within Microsoft's ecosystem is one of its strong points.

There are a few areas where Microsoft Power BI could be improved. For instance, spatial data support should be enhanced. Currently, it supports only topoJSON format for spatial files; other formats such as shapefiles or KML should also be supported to broaden the library.

I have been using Microsoft Power BI for at least five years.

The stability of Microsoft Power BI is quite good. I would rate it a nine out of ten. However, there can be some difficulty in handling very large datasets, but overall, the stability is strong.

Dealing with very large datasets can be a bit difficult, which impacts the scalability to some extent.

I would rate Microsoft's customer support a seven out of ten. This rating may be influenced by my location in Turkey, making access to support somewhat challenging.

Neutral

I have used several other solutions, including Tableau and Looker. Each has its advantages, but generally, I prefer Microsoft Power BI first, followed by Qlik, and then Tableau.

The initial setup of Microsoft Power BI is straightforward and can be managed without significant issues. Using it for academic purposes, we mainly use the desktop version.

For companies, the program is cost-efficient. Academically, we use Microsoft Power BI for free through the licenses provided.

I evaluated Tableau, Looker, and Qlik before deciding on Microsoft Power BI. Each of these solutions has its own unique advantages.

Given the increasing need to analyze large datasets, I would definitely recommend Microsoft Power BI. It is a valuable tool for both academic and practical applications, particularly for those involved in data analysis and IT studies.

I'd rate the solution eight out of ten. 

On-premises

We have created the reports and are continuing to work on them. We are deploying them to the proxy, and the users are utilizing them for various business processes.

I work in Tableau or Tableau and Power BI. It can handle large data sets. You can just get the raw data. When it comes to Power BI, if you have to get the raw data and want to refresh it, the refresh at a point in time would degrade performance.

One of the key benefits of Power BI is how easy it is to develop reports. Even non-technical users can easily download the report and learn to include slicers and data filters once provided with a template. The platform is very user-friendly. Another advantage of Power BI is that if the report developer encounters any issues, they can quickly find solutions through Microsoft’s help resources. You can get your assistance by visiting the Microsoft support site or posting queries. This makes developing and delivering reports much easier. Microsoft Power BI provides much support and flexibility, making it a great tool for report generation.

It can integrate with different data sources. You can connect seamlessly to Databricks, SQL Data Warehouse, third-party sites, and multiple other sources.

We identified a couple of issues in the reports. Some reports took too long to load, particularly at the end of our data refresh. To address this, we optimized the data model using multiple tables, improving performance. Now, all reports are refreshing properly using DBP, and we’ve implemented these improvements in Power BI.

I have been using Microsoft Power BI for two years.

The availability of Power BI is excellent. Once a user is set up, they can easily access and work with the Power BI files from the repository. There are also various modes for adding features, allowing users to combine data in different ways to make informed business decisions. 

Based on business discussions, there are 25 to 100 business users. The users work with templates, and we collect UAT feedback from them.

The initial setup was straightforward. Based on the current requirements, I've been able to develop the reports independently. It's easy to use and allows for faster reporting.

Once we generate the reports, we schedule and publish them on the website and then share the process with the users.

We're able to refresh the Power BI reports and create data models to support the business at this stage.

I'm working with a company that manages detailed sales data for the clothing industry. We're tracking orders, brands, seasons, and which facility handled the order, along with audits. We're focusing on metrics like fabric consumption and fiber content for reporting. 

We can develop reports in Power BI, including RxTx reports. Many of the business teams are also using Power BI. For support, we use Slack to manage tickets and TableLab for some tasks. Power BI offers a trial version, and you can get a pro license at a relatively low cost, with users having access to AV accounts. The main advantages are that it’s easy to use and more affordable compared to other reporting tools.

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

Public Cloud

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.

Public Cloud

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.

Other