We changed our name from IT Central Station: Here's why
Get our free report covering Tableau, Microsoft, Qlik, and other competitors of IBM Cognos. Updated: January 2022.
564,322 professionals have used our research since 2012.

Read reviews of IBM Cognos alternatives and competitors

Global Head of Professional Services at a tech services company with 11-50 employees
Real User
Top 20
Provides ease of getting something up quickly, but some of the more advanced modeling techniques are fairly difficult to do
Pros and Cons
  • "The number one thing was just the ease of getting something up quickly. The other thing that was good about it was that it was fairly fast for decent-sized data sets in terms of performance and run time."
  • "From a downside perspective, some of the more advanced modeling techniques are actually fairly difficult to do. In addition, I just fundamentally disagree with the way you have to implement them because you can get incorrect answers in some cases."

What is our primary use case?

It was for dashboards. The key use case was for creating visibility to performance metrics for the leadership team. It was the most recent version, and it was deployed on-prem. 

How has it helped my organization?

The key use case that we were going after very specifically created visibility to performance metrics for the leadership team. So, it allowed us to give that common view of performance metrics and drive business conversations based on the common shared set of facts. We were able to expose data and relationships that we otherwise couldn't do in our enterprise system silos. From that perspective, we were incredibly successful in really driving performance. When you combine that with some real championing in the business and with some leadership to push it down, the fact that it was Tableau wasn't as relevant as the fact that we had the championing pushing the process and pushing it down.

What is most valuable?

The number one thing was just the ease of getting something up quickly. The other thing that was good about it was that it was fairly fast for decent-sized data sets in terms of performance and run time.

What needs improvement?

From a downside perspective, some of the more advanced modeling techniques are actually fairly difficult to do. In addition, I just fundamentally disagree with the way you have to implement them because you can get incorrect answers in some cases.

One of the key challenges is that you never know whether it is how your developers developed it or whether it was the tool. We did find that once we got into more complex models, the ability to keep objects that should tally the same way but didn't became more and more difficult. That was probably the big thing for me. I don't know enough about how the tool was developed to know whether that was because they didn't follow a recommended practice. That was probably the number one thing that I found frustrating with it.

When we started to try and get into some very granular data sets that had some complex relationships in them, the performance on it degraded pretty quickly. It did degrade to such an extent that we couldn't use it. We had to change what we were trying to do and manage its scope so that we could get what we wanted out of it or reduce the scope of what we needed out of it. It doesn't have a database behind it, per se. So, while doing some of the more complicated things that you might otherwise do on a database, we started hitting some pretty significant challenges.

For how long have I used the solution?

I used it for about three years.

What do I think about the stability of the solution?

Tableau worked fairly well for straightforward data sets, but it struggled when we got into the more complicated data sets and larger data sets. 

What do I think about the scalability of the solution?

We were able to deploy it fairly broadly without a whole bunch of work. From that perspective, it worked fine. I was deploying my stuff to about 200 users across Canada, and I don't think we saw a blip on the server when people logged in. It was fine. If we were to roll out some of the bigger applications broadly, like the ones that we were having performance challenges with, we probably would have crushed the box. We would have had to get more CPU. Most likely, it would have been a memory issue, but we never hit that inflection point.

There were about 200 users of the solution. It went all the way from the equivalent of a senior vice president and all the way down to the equivalent of a line manager. So, we had business unit leaders, vice presidents, and operational managers.

It was being used extensively for a specific use case. There were lots of other use cases that it could be used for, but there needs to be an appetite from leadership to go, drive, and commit resources to go do that.

How are customer service and technical support?

I didn't have to deal with technical support. Mr. Google is pretty good on the topic.

Which solution did I use previously and why did I switch?

We had previously used Cognos to do the exact same thing. The only reason why we replaced it was that the business decided to go towards Tableau. Otherwise, there really wasn't any real reason to replace it. It was probably a little bit easier and more interesting for people to learn and to develop applications in the program than in Cognos. The ramp-up time to get to reasonably proficient in Tableau plus the support through Mr. Google made it a lot easier for me to get resources and do development on Tableau as compared to Cognos.

The organization decided to move away from the old platform. So, basically, I was lost when they asked me to shift off so that they could shut it down. I personally prefer the previous platform. I understood it very well. I had used it for years, and it worked just fine. For the most part, the challenges that we had on the old platform were not resolved by Tableau, which just reinforced to me that it wasn't a tool problem. It was a people problem.

How was the initial setup?

It was pretty straightforward. The big thing that confuses people in a project that involves Tableau is that Tableau is a very visible but small component of the overall solution. That's because 80% of the work is data. It is not Tableau. So, Tableau is actually a fairly small component over that overall solution. It took a few days to get it up and going. Almost 80% of the work is actually on the data side, which takes forever, but the actual Tableau component of it was pretty straightforward. It was not that difficult.

You can get a Tableau dashboard up on a weekend. It is not hard to get something up and running. It is pretty trivial. It isn't any more or less difficult than any other tool to get up and going. I've used a number of them, and they're all pretty easy to get up and going. Tableau was the first one out of the gate with this democratized data perspective, where they were going to do departmental BI and up to enterprise BI years ago. Now, they now charge a fairly hefty premium to leverage that product. It is not a cheap product.

In terms of maintenance, it can take as much or as little as you want because it just runs. So, technically, you don't have to have anybody to do very much. You just need a very skeleton crew to operate as is. The challenge that you run into with solutions like this is that you need to continue to refresh the information with new and different views because people want to know more, and they want to go deeper into it. It is not a function of the technology. It is a function of the use case. So, you tend to have lots of new requests for new reports and analysis, and that's where you tend to have more challenges.

We didn't get into analysis users who are able to sort of do a little bit more themselves. There were viewer licenses where you are just using preset reports, but there are obviously additional training and things like that, and you have to deal with it if you start getting into more advanced power users.

What about the implementation team?

I was at another company, and we were the integrator.

What's my experience with pricing, setup cost, and licensing?

It is fairly expensive. I have no idea what they paid. We were on an enterprise license, so whatever it is they licensed at the enterprise level is what we paid.

What other advice do I have?

A good chunk of it has got nothing to do with the tool. It has everything to do with your leadership and your governance requiring it. We had our IT team roll up Tableau multiple times and not a single person used it because there just wasn't enough leadership support to use it. There is nothing wrong with the tool, and it worked fine for what it did, but every time I logged into it, I go, "Okay, but what did you want me to actually do with this? I see all this information. I understand it clearly. I'm not sure what I do with it though." So, without that additional guidance from leadership, rolling it out is irrelevant. You need to have that strategic leadership associated with it.

The key piece of advice would be that you got to look beyond your tool. You need to look at how you're going to get this information used in your organization. What kind of leadership support, governance support, and ongoing support are you going to have? It is all based on trusted data. The value of the tool is based on the quality of your data and the leadership's support to use it. So, if you don't have high-quality data and you don't have leadership support to use the data, you don't need any tool because nobody is going to use it.

I would rate Tableau a seven out of 10. It suits the purpose, but in and of itself, I don't think it is significantly better or worse than its key competitors.

Which deployment model are you using for this solution?

On-premises
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Flag as inappropriate
Santosh  Pallai
Sr Consultant at a tech services company with 1,001-5,000 employees
Consultant
Top 5
Enables us to allocate, spread, and distribute actual figures
Pros and Cons
  • "In the most recent release, the schedule publication was officially updated and it's been added on MS Office 365. I like how we had an EPM for B to C perspective; it's a great enhancement. Also, I believe the B to B connectivity has been improved. Android support for mobile is really good also. Power BI has always had android support in place, so manual support for SAP Analytics Cloud is also a very good feature."
  • "Custom visuals is another area of improvement. There are also some mobile features that are missing. There are features that aren't available on the mobile."

What is our primary use case?

My VP asked me to work with my plan number to figure out how to increase and support our sales region. On the planning admin, I created a model and then imported actual and forecasted data. From that, I was able to determine the variance. We managed to plan this with small amounts of data. 

We created a planning model and enabled it to make a planning checkmark that works with the time category in the tab dimension, in order to bring it down to the lowest granularity, by month, start date, and end date. 

We created an organization dimension. A responsible person to monitor each region is required. Then you can drag and drop the region hierarchy from the parent.

Then, we worked on the calculated numbers, for example, the gross margin, which was the total revenue minus COGS. We then divided that number by total revenue times one hundred. From there, we could pull the data from the file and select source actuality to validate it. 

We performed all of this using SAP Analytics Cloud.

How has it helped my organization?

In the most recent release, the schedule publication was officially updated and it's been added on MS Office 365. I like how we had an EPM for B to C perspective; it's a great enhancement. Also, I believe the B to B connectivity has been improved. Android support for mobile is really good also. Power BI has always had android support in place, so manual support for SAP Analytics Cloud is also a very good feature.

Smart Insights have also been enhanced, especially in regards to the Stories.

Apart from that, I would like to see more data-handling enhancement. Smart planning can give us immediate results.  When we come to analytics, If we could get more enhancement, we could probably completely skip the data warehousing concepts. This would be a big improvement.

With all of the new updates, now we can combine different types of data together and give our customers a full picture. 

I am happy with the new release that is coming out. It's comparatively a little slower than the version we had from 2019-2020; however, the enhancements they have added are much better than previous versions.

What is most valuable?

The most valuable feature is that we can allocate, spread, and distribute the actual figures.

What needs improvement?

The cost is an area that could be improved. I also think that Ofice 365 should be incorporated. People would find it to be more user-friendly with Office 365 integrated. Flat file integration can be a distinguishing factor.

Custom visuals is another area of improvement. There are also some mobile features that are missing. There are features that aren't available on the mobile. 

There should also be better connectivity tools for HANA and Success Factors. They have minimal visualization relations and they have the third-party add-ins.

For how long have I used the solution?

I have been using this solution for the past six months.

What do I think about the stability of the solution?

We have 300-plus Stories that we already had in the system, that we had to do performance tuning. I brought it down to 267, to be exact. We had over 302 dashboards and then we brought it down to 111 stories on 267 visualizations. When we have too many pages, the performance gets impacted a little on the initialization part. When we open the story, it takes a little bit of time because it's not on-premise. Because our clients are based in the Netherlands and we are based in Bangalore, we had to manage the different time zones, and the business hours are different. We had to find out during the peak business hour how the SSE behaves.

We found that in the peak business hours it does slow down a little bit, considering the internet speed and everything. We did take everything into account. Then we checked the performance and the data also. In order to be competitive with the other software in the market, a little enhancement in this part also would give the upper hand compared to other BI tools.

What do I think about the scalability of the solution?

We used to go in a cognitive window wherein we don't have any caches in place, so that we could get an accurate picture of the performance. But we also want to reduce the number of filters, and then we want to do more slicing and dicing across the data and try to see how it improves. In the near future, we would try to test the data more.

It performs quite well. Custom visuals would definitely help us to improve a little more. 

There are more viewer licenses. We have got close to 130 users for Analytics Cloud. And for developer access, for read and write, at our location we have around six plus two for planning, altogether 11 to 12 licenses. 

We have BW HANA. So we have only four developers as of now. We used it more extensively before the pandemic but not as much now. We do have plans to increase usage in the near future. 

How are customer service and technical support?

The technical support is quite good. Any time there is a new release and we have any issues, we connect with the technical support team and then go ahead and write about it in a blog so that the other users can also get help for similar issues. 

Which solution did I use previously and why did I switch?

We previously used Cognos Analytics and Tableau. I've done a couple of POCs on Tableau and worked on micro-strategy. We switched to SAP Analytics Cloud primarily for the planning, development, and the user-friendliness. When SAP comes up with a solution, they definitely try to be up to market. The features were not in a premature stage. We had faith that SAP had enhanced features compared to other BI tools.

How was the initial setup?

The initial setup was pretty easy. It was also easy for my team. They thought it was easy to install. There's no download, there was no complexity.

What about the implementation team?

We do the maintenance for it because we know the ins and outs of the development. We also do the admin.

What other advice do I have?

If you are new to SSE and are trying to implement SSE in your project, don't think that SSE is an SAP product. Look into the features because I am sure you'll be satisfied with the features. They come out with the releases. I go into the release notes to understand what are the enhancements are. This will make it easier to understand. 

If you have somebody who isn't as experienced with BI, even that person can still learn SSE and can cope up with the BI requirements. In India, if you want to be a BI compatible, you have to have at least three years' experience so that you can understand all of the data warehousing concepts, and EDL. With SSE, learning is very smooth and easy.

I would rate it a nine out of ten. 

The missing point would be because of the performance. 

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Information Architect at a government with 10,001+ employees
Real User
A simple, flexible, low-code, and scalable solution for data integration and modeling
Pros and Cons
  • "It is a pretty straightforward and flexible solution for data integration and modeling. It is a low-code solution. When you are doing data integration, you can use the GUI, which is very simple and straightforward. You can also do very intricate custom queries and model it at different levels. It is very easy to use and scalable."
  • "It is kept very current, and there is an update literally every month. However, the interface changes quite randomly with no documentation, which is difficult at the domain and architectural level where you're planning things and engaging the business. Things change frequently, and you wonder where has the button for the new report gone. They should provide better documentation on interface changes. It should be better optimized. It is supposed to be a data integration tool, but it is doing relatively simple queries. It has its limitations. For example, you can only pull a number of columns. So, there is room for optimization on its ability to integrate multiple data sources. The desktop tool is very memory-intensive, and again, this is not documented clearly. It requires a heavy CPU and memory use, and it causes your operating systems to become unstable. I would like to see the ability to create datasets within Power BI. Microsoft is promoting Azure as a cloud solution, but it is dependent upon a desktop component, which seems a little bit deceptive. Data set is the basic element that you report from, but it has to be created on the desktop and then published to the cloud. So, you're in the cloud, and you create a data structure or the data flow, but you can't report from that. You have to leave the cloud, go to your desktop, create the data set on your desktop, and publish it to the cloud. You go back to the cloud and create your report by using that published data set, which is very non-intuitive. If you go to the Microsoft Power BI community, this is a common complaint across the entire community."

What is our primary use case?

We are using it for reporting, analytics, and data science. We have its latest version.

How has it helped my organization?

Microsoft's CRM platform has very limited reporting capabilities. Power BI was able to meet the business requirements for reporting and more in-depth analytics. It is a part of the Microsoft Ecosystem, and there is a straightforward connection from Power BI to CRM. 

What is most valuable?

It is a pretty straightforward and flexible solution for data integration and modeling. It is a low-code solution. When you are doing data integration, you can use the GUI, which is very simple and straightforward. You can also do very intricate custom queries and model it at different levels. It is very easy to use and scalable. 

What needs improvement?

It is kept very current, and there is an update literally every month. However, the interface changes quite randomly with no documentation, which is difficult at the domain and architectural level where you're planning things and engaging the business. Things change frequently, and you wonder where has the button for the new report gone. They should provide better documentation on interface changes.

It should be better optimized. It is supposed to be a data integration tool, but it is doing relatively simple queries. It has its limitations. For example, you can only pull a number of columns. So, there is room for optimization on its ability to integrate multiple data sources. 

The desktop tool is very memory-intensive, and again, this is not documented clearly. It requires a heavy CPU and memory use, and it causes your operating systems to become unstable.

I would like to see the ability to create datasets within Power BI. Microsoft is promoting Azure as a cloud solution, but it is dependent upon a desktop component, which seems a little bit deceptive. Data set is the basic element that you report from, but it has to be created on the desktop and then published to the cloud. So, you're in the cloud, and you create a data structure or the data flow, but you can't report from that. You have to leave the cloud, go to your desktop, create the data set on your desktop, and publish it to the cloud. You go back to the cloud and create your report by using that published data set, which is very non-intuitive. If you go to the Microsoft Power BI community, this is a common complaint across the entire community.

For how long have I used the solution?

I have been using this solution for about 18 months.

What do I think about the stability of the solution?

It is pretty stable. I haven't determined any major issues.

What do I think about the scalability of the solution?

It is very scalable. It fits perfectly with the larger Azure Data Lake reference architecture. Power BI platform is a fundamental piece, and it becomes scalable to use with other components within that reference architecture.

We're in the process of laying out a three-phase approach. Over the next year, its usage will increase from 50% to 75%. In terms of the number of users, we have around 150 users who are data scientists and data analysts. We have around 5,500 desktop users, and it is a part of 365, which is on every desktop. 

How are customer service and technical support?

There is a lot of online support. We also have Microsoft consultants on contract, and the support comes through them. Their support is very good.

Which solution did I use previously and why did I switch?

We also have IBM Cognos. We haven't switched. They're being used in tandem. There are different sets of requirements for two different solutions. 

How was the initial setup?

I wasn't part of the deployment, but my understanding is that it was pretty straightforward.

What about the implementation team?

We used a Microsoft consultant for implementation. Our experience was good. We don't have any maintenance crew.

What other advice do I have?

I would rate Microsoft BI a nine out of ten.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Manager at a tech services company with 501-1,000 employees
Real User
Top 5Leaderboard
A complete platform with prebuilt applications, good scalability and value for money, and a toolkit for no-code development environment
Pros and Cons
  • "It is very easy to use. It has got what they call a toolkit, which is a no-code development environment. You can develop a whole solution with it because it is a complete platform. There is a lot of online material that can be used as a reference. You can help yourself while developing a solution. There are some prebuilt applications in the platform environment. You can very easily customize and integrate these applications. It also has flexible scaling of machine resources, which is really great."
  • "It can have more functionality for narrative reporting. They should also improve their training courses, which are currently very lightweight. When you get into more complex things, it is quite difficult to figure out what you're supposed to do, and you have to look at a lot of videos before you actually understand, which is a bit frustrating. Their training can be more comprehensive."

What is our primary use case?

It can be used for business intelligence, predictive planning, financial consolidation, integrated planning, budgeting and forecasting, strategy execution, and management. It can be deployed on the cloud or on-prem.

What is most valuable?

It is very easy to use. It has got what they call a toolkit, which is a no-code development environment. You can develop a whole solution with it because it is a complete platform. There is a lot of online material that can be used as a reference. You can help yourself while developing a solution. 

There are some prebuilt applications in the platform environment. You can very easily customize and integrate these applications. It also has flexible scaling of machine resources, which is really great. 

What needs improvement?

It can have more functionality for narrative reporting. They should also improve their training courses, which are currently very lightweight. When you get into more complex things, it is quite difficult to figure out what you're supposed to do, and you have to look at a lot of videos before you actually understand, which is a bit frustrating. Their training can be more comprehensive.

For how long have I used the solution?

I have been using this solution for one year.

What do I think about the stability of the solution?

It is stable.

What do I think about the scalability of the solution?

Its scalability is good. Because of the agreement that they've got with Microsoft Azure, they monitor the performance and scale automatically. If more processing power is required, they just add it. You don't have to worry about that, and you also don't have to pay extra. 

In terms of usage, we started with four or five people. We currently have about 30 users, and we will use it for more areas of the business.

How are customer service and technical support?

Their support was good. They got back to us and helped us immediately. I can't complain.

Which solution did I use previously and why did I switch?

We have used Power BI and Cognos.

How was the initial setup?

We use it in the cloud, so we didn't have to install anything. It took two days to get our environment provisions up and running. 

What's my experience with pricing, setup cost, and licensing?

It is not the cheapest product on earth, but you get so much. It provides good value for money.

What other advice do I have?

I would rate Board a nine out of ten. In general, it is a surprisingly good tool.

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Flag as inappropriate
Get our free report covering Tableau, Microsoft, Qlik, and other competitors of IBM Cognos. Updated: January 2022.
564,322 professionals have used our research since 2012.