Tableau Enterprise Reviews

I primarily use Tableau for fair-market reporting.

I've been using it a lot for our dashboarding needs, circulating data to the business, generating PDFs, and publishing on the portal.

Over the time that I have used this solution, I've found the interface to be extremely user-friendly.

I especially like the flexibility that Tableau provides. You can quickly make web edits from version 9.0 onwards. My understanding is that Tableau 2020 has many more features for this, as well.

I customize the reports to my needs and preferences.

There is a lot of APIs available, which means that Tableau can be customized to a large extent.

Tableau had some issues with parameters. In particular, prior to version 2020, they did not have dynamic parameters.

Tableau cannot work with cubes or MDX (multidimensional expressions).

For enterprise-level users that are computing millions of records, they need to improve the features.

I have been using Tableau for close to five years.

In all aspects, Tableau has been very stable.

When there are millions of records, scaling up is quite difficult. There are, however, workarounds.

For example, you have to create summary tables or aggregate tables so that Tableau can be faster. There are third-party solutions like Kyvos available but if Tableau can integrate that and address the scalability, then it'll be an undisputed champion in the space.

Technical support is extremely good. Since we have been a customer of Tableau, they have always responded really well to our queries. This is true regarding price, as well as in the technical aspect.

They have a good knowledge forum.

I have worked with SAP BusinessObjects, Domo, SAP, and Birst.

One of the reasons that I prefer Tableau is that it's very user-friendly. Anyone who is familiar with Excel can easily adapt to Tableau.

We have been using Tableau for a long time, and we have seen a return on investment. The reason is that we have been able to scale it up to an enterprise level.

In the long run, there is definitely a return on investment.

Licensing is slightly on the higher side compared to other products, such as Birst. There are different licensing options so you really have to be careful when choosing them. I recommend that you discuss your needs with the salesperson and try to negotiate the price.

In general, the price is slightly higher than products such as Power BI and Birst.

Tableau is a solution that is near-perfect.

I would rate this solution a nine out of ten.

Tableau is used for reporting time in the dashboard and also for skills in maintenance and metrics. That's pretty much it.

The dashboards are great.

The solution offers very good reporting.

It's a stable solution. We've never had any issues with it.

We have found the scalability to be good.

There are no significant improvements needed. 

It would be nice to include more features on each dashboard. 

I've been using the solution for a couple of years. I've used it for a while at this point.

The stability and reliability are good. There are no bugs or glitches. It doesn't crash or freeze. 

The solution is scalable. It's not difficult to expand it to your needs.

We are a really big company. I'm not sure exactly how many people actually use the solution. In our department alone there are at least 50 users. That's a small team, really. I'm sure it's used extensively globally.

I have not heard of plans to increase usage in the future. 

I don't have experience with technical support. I can't speak to how helpful or responsive they are as I've never been in contact with them.

This product was already in place when I was hired. I'm not sure if something different was used previously.

The installation was handled before I came on board. I was not a part of a process. I can't speak to if it was difficult or not.

It's a hosted solution. We don't need a team of engineers on it from our end.

I can't speak to the pricing. We're a global company. Another team deals directly with contracts. 

I would rate the solution at an eight out of ten based on my experience and what I know. 

We use it for internal monitoring purposes.

I like Tableau a lot as its visualizations are great; there's no doubt about it. It's easy to use. 

The look and feel and features are very good. Dashboarding is very good.

The product has been stable. 

While my experience has been mostly positive, there are certain limitations, as every tool has.

If I have to develop any, for example, pie charts, I can develop them just fine. However, if I have to develop a donut chart, that I cannot do it in a simple way. There are tricks that I need to use if I have to design a donut chart. It should be more flexible and provide more visualization options.

It does not provide detailed reporting like other reporting tools such as Microstrategy or Cognos, or other enterprise reporting solutions.

If they could provide better reporting as well as visualization, it would be a perfect product.

Pricing is a major thing. If someone has to use it within an organization, it is not that cost-effective, especially when a competitor like Power BI or some other reporting tool comes almost free along with their cloud solution. If someone is opting for any cloud solution, any cloud platform, especially if I talk about Microsoft, they will give you Power BI almost free of cost, or at a minimal cost. In such scenarios, people would prefer using Power BI or a similar kind of tool rather than using Tableau. That is a major concern which Tableau should look into.

I haven't been using it continuously, however, I started using Tableau around six years back. Since then, there have been two projects in which I worked on Tableau. I did work with it in 2021.

The stability has been good. there are no bugs or glitches. It doesn't crash or freeze. It's reliable. 

I'm not managing any scaling aspects. I'm basically from the development team. Every company has its own scaling goals. In my company, I don't really follow that aspect.

I can't say how widely used it is in my organization. When we deploy a tool, there are different teams. There are different stakeholders who are actually using it. I manage my team. I know about only my team, not other teams.

I'm not part of that team that manages the setup. I cannot comment on that.

As far as ROI goes, I'm not directly aware of it, however, likely you can Google statistics. 

The pricing can't compete with Microsoft, for example, which basically gives their BI product away for free to those that purchase cloud products.

I'm also aware of solutions such as Microsoft BI, which is bundled into Microsoft Cloud products. It makes it less expensive for users if they are already heavily using Microsoft.

I'm a customer and an end-user.

I'd rate the solution at an eight out of ten. 

We have Tableau installed in a massive environment. The Tableau sector is on a seven-cluster node, including one with two nodes for high availability. In our initial setup, Tableau was deployed across the entire infrastructure, so that's more than a hundred sites and around 30,000 active users, and each site has several projects, too. We have around 11,000 workbooks in total.

The maintenance of the entire infrastructure is done on-premises, including user management, authentication, authorization, permissions, and publication. We are constantly doing these tasks, including the SSL certificate renewals. 

Tableau is an advanced specialized tool. One of the best features I've seen is the lack of an intermediate semantic layer. I think that's an advantage compared to any other tool like BusinessObjects or Power BI, which are Tableau's biggest competitors. All of these have semantic layering, so the learning curve is high. Users have to understand the data model and the relationships, but Tableau has no data model, so you only need to know the relationships of the direct inquiry to build a report. 

I've been using Tableau for about six or seven years.

Tableau is stable, and I believe stability is essential. Our infrastructure has been set up right. The last two updates have had very few bugs, so stability-wise, it is excellent. However, performance is something we need to investigate further. It's hard to say whether performance problems are on the Tableau side or an issue with the infrastructure or the data sources. If there is a performance issue, we can't identify precisely where the problem is. 

The scalability is good. We already have some help from professional services, and we've conducted an analysis showing that the number of users will be increasing every year.

Tableau support could be improved.

I've worked with SAP BusinessObjects. Tableau is a visualization tool built into the infrastructure for doing analysis. That's Tableau's focus. BusinessObjects is for doing analysis of some data and then sharing it on the server. 

BusinessObjects is an enterprise tool that needs an extensive infrastructure. It requires a proper IT team to configure the semantic layer and the universal support and then build the report. And the most significant advantage enterprise tools have is pixel-perfect reporting. You can create a pixel-perfect report and share it as a PDF or Excel file with the same format. Tableau is more or less a self-service analytics tool, so we do not have those kinds of features. There are a good amount of differences between these two.

Setting up Tableau is straightforward, and I don't think it took long. It took maybe a day or two for the installation and migration and all that. However, the planning took some time because we worked with professional services. Planning took maybe 40 hours. Tableau requires a good deal of maintenance. We have a team of about five or six people for the administration.

We had professional services to help us.

SAP and Tableau have different pricing models. Their code-based license is around $13 to $15 per year. I don't think Tableau has a code-based licensing model at all, so those enterprise tools are on the higher side.But on the other hand, Power BI is on the cheaper side compared to Tableau. Power BI is much more affordable and also good.

I rate Tableau eight out of 10. 

I work in the hospitality industry and I use Tableau Online and Tableau Bridge with our food ordering company. In our specific uses, I have found that Tableau is very good for extracting data, rather than for working live on the data.

Although the process of transferring data to Tableau isn't the best, once the data is already on Tableau, it works completely fine. I will typically make use of layer aggregation and other operations such as slicing and analyzing it by getting right inside the data in various ways.

Due to the demands of our industry, we always have things that we would like to see more in-depth over different dimensions, such as restaurants, branches, cities, and so on. With Tableau's help, our company can aggregate all the raw data and then analyze by rows, to see, for instance, which restaurant is doing the best by comparing them with one another. It also enables us to easily split areas into zones and use the data to test for not only which restaurants are doing the best, but also where (i.e. in which cities and branches). 

Although Tableau isn't the best for us when it comes to processing and working on live data, it is very good at extracting data for analysis. Once you have extracted the data, the aggregate layers you can create, along with slicing and other operations, are very handy. It allows us to really get inside the data, and it is, in my opinion, better than any other tool I have used with the same pricing model.

Of the best analysis features, multi-aggregation layers come out on top for me, because they let you extract raw details while making multiple aggregations on different time levels and different dimensions, and you still manage to get your work done quickly without having to load a lot of data grouped over different dimensions.

Tableau Bridge is also a very good tool, however I can tell that it does need a few fixes and some maintenance. That said, it's still good for its first few years since release.

Most of the problems in Tableau Online that I have noticed have to do with performance or weird, inexplicable bugs that I can't pin down. For example, you might try unloading some data, and you'll be waiting for a long time without anything happening.

These bugs always seem to happen when we perform big upgrades or do maintenance work, and we have had to send a lot of tickets for unexplained issues during these times. It doesn't seem to be a problem only for us, but also for customers all over the world, such as in Ireland, Western Europe, Eastern Europe, and the US, too.

As for future features, I would like to see major upgrades in Bridge and the Flow Tool, allowing us to do more data engineering work. I think it would give Tableau a big edge in the market to look into how to incorporate more data engineering tools into their product. 

Besides that, I would also like the charts to be more realistic and easier on the eyes.

I have been using Tableau Online for three years now.

The stability is okay. It's not 24/7, but you can say it's stable enough. In the start, it's more stable, especially compared to our OBIEE problems, which have taken two or three days to solve in the past.

It's easy to contact Tableau and ask to increase users or resources. They'll do it in the blink of an eye.

At present, we have 20 users, 12 of which are shift users. The majority of our users in total are board members or high-level managers. 

I wouldn't give their support more than a seven out of ten rating.

I have previously used Power BI, Qlik Sense, and Qlikview. I switched because Tableau was better in working with different sources compared to Power BI which was the only one that was truly on par. Qlik Sense and QlikView were easy to use but didn't have most of the features that Tableau and Power BI offered. Then there's OBIEE which I have used for the past two years, but it is quite difficult for non-technical users.

I also didn't like that Power BI is typically coupled with Microsoft Azure, whereas Tableau works well with AWS and Google which are a lot easier. 

The setup is straightforward. I mean, there's not much setup at all. It's easy for any mid-level user to do it. For example, I just used the documentation they provided and did everything myself. The documentation was sufficient
and the implementation strategy doesn't take more than 20 days.

I implemented Tableau by myself using the documentation they have made available. And for maintenance on one single node, you might need only two to three people involved.

For data extraction and analysis, Tableau is better than any other tool I have used with the same pricing model.

My ultimate advice is that you should know what the tool is capable of first and what your needs are. I think it's better to use the Server edition, and not Cloud, because there are a lot of problems in the Cloud version that don't seem to be present in the Server version. As for myself, I will likely switch to Tableau Server next year after doing a bit more research on how to do the changeover.

I would rate Tableau an eight out of ten.

When we work with CXOs to create dashboards we use Tableau. C-level employees like a CXO, a CEO, a VP, prefer to work with Tableau. It's easier and better for them.

For Tableau, the most valuable feature is the user experience and the quality of the end product.

One thing I would want to change for Tableau is to have a lower-cost model. It's pretty high for enterprise deployment.

In the next release, I would like to have the capability to call machine learning models within Python while I'm building a dashboard. The value calculation should be a machine learning model, which is running somewhere else, on say, Amazon. These tools give good outputs, like calculated fields and all. But today the outputs are not straightforward. In simple terms, I need machine learning on the fly. That is not there.

I have been using the solution for four or five years.

I would say the solution is very stable. We have not had any issues in using the product at all.

The solution does have scalability issues. When the data size increases, the product slows down and doesn't work right. In addition, it's very expensive to scale.

The only other solution we use and have explored is Power BI from Microsoft.

The solution deployment was pretty simple and straightforward.

We deployed the solution with our in-house team.

It's an enterprise solution, and we have all licenses. Tableau has multiple licenses; there is a reader, a developer, and an administrator.

If there are 50 or 100 users wanting to use Tableau, it's pretty expensive. The license is very expensive. We have 20 to 30 users in our company.

Because the solution is a drag and drop tool and what unique features we need or what we want to build, we cannot build using the tool. So we use JavaScript for that. We write our own code and build our own solutions.

My advice would be that all solutions are good, but it depends on your use case. If you are building something for C-level employees, use Tableau or another solution.

I would rate this solution an eight out of ten.

We use Tableau for data analysis. We integrate 15 sources of data and then that data is brought into AWS. From the AWS, the data is uploaded onto a dedicated Tableau server where we have all our dashboards running. We then run code on the data to return results, such as the regression and causation.

The solution has great features which nobody can beat, you can do a lot of customizations, such as use different dimensions and colorize them. Additionally, you can use the numeric values for the customization, which is an exceptional feature.

There is a lack of visualization in Tableau which could be improved. For example, if you want to do a Sankey in Tableau, you have to do a lot of work to do it. Sankeys are available, they are for sale for a minimum of $400, which is out of the question. Whereas if I wanted to do a Sankey, it is simple for me to use a free visualization and put in the data, and from what I already have, receive a fancy Sankey.

Whenever it comes to specialized visualization, Tableau is an absolute failure.

The integration between Tableau and our statistics software or other software, such as Python is very loose and undefined. If they improve that it would be a benefit.

I have been using Tableau for approximately two years.

The solution is stable.

If I have web analytic data on session IDs, Tableau or Power BI both fail miserably in scalability because you are not able to go on a session-level and have 18 million rows fire up visually.

We have approximately 100 users using the solution.

The initial setup is simple.

We had a local team of two technicians that do the implementation and maintenance of the solution.

We are on an annual license which costs us $1,400 which is very expensive. Microsft BI is less expensive.

I have evaluated Microsoft BI.

The reason why we are not getting rid of Tableau is because of legacy reasons. Legacy, meaning it is being carried over and our organization does not have time and energy to transfer everything to Microsoft BI.

I will not give any credit to Tableau or Power BI for the very simple reason that everything is in the hands of the developer of how you visualize the data. There is not any magic in what Tableau is doing, the magic is from the developers who are creating the visualization. Any visualization tool which gives that capability sets you apart.

I would not use Tableau if I am working out of a financial organization because it is lacking fancy visualization. However, if I was a bank or a government organization where I am only looking at trend charts and bar charts I think Tableau comes out ahead of other solutions, such as Microsoft BI.

I rate Tableau a five out of ten.

We use the most recent version. 

We use the solution to engage the field teams and we integrate that with the data warehouse data and build the dashboards for them.

It is helpful that the solution provides access to one's own data. It allows a person to get insights out of the data provided by his tool, based upon the KPIs that the person wishes to look at. It all depends upon different use cases. We have dashboards for marketing people, field teams and executives. It all depends upon which insights a person wants, in which case he can prep the data accordingly. This is good. 

The most valuable features are the visualizations, the way they show the combination charts. This allows a person to jointly put in different measures in different axes and greatly facilitates the user in understanding the data better.

There should be a focus on memory data, which is the concept of Tableau. This is where they squeeze the data into their memory. Because of that, we see performance issues on the dashboards. The architecture should be improved in such a way that the data can be better handled, like we see in the market tools, such as Domo, in which everything is cloud-based. We did a POC in which we compared Tableau with Domo and performance-wise the latter is much better.  

As such, the architecture should be improved to better handle the data.

We are seeing a shift from Tableau to Power BI, towards which most users are gravitating. This owes itself to the ease of use and their mindset of making use of Excel. Power BI offers greater ease of use. 

For the most part, when comparing all the BI tools, one sees that they work in the same format. But, if a single one must be chosen, one sees that his data can be integrated at a better place. Take real time data, for example. I know that they have the live connection, but, still, they can improve that data modeling space better.

We have been working with Tableau for almost seven years.

The solution has pretty good stability. It's a robust tool, even though it has a steep learning curve. But, still, I feel that from the stability perspective, it's a leading BI tool in the market. It's pretty stable.

I personally don't like any BI tool to have that scalability. What we usually do is integrate scalability into our warehouse layer. We know how to scale up and down and we handle it there. We don't rely much on the BI tools to do that.

I am talking about the scalability of a program in general, be it in its relation with users or as it concerns dashboards. 

We recently started working with Tableau online and that particular solution is scalable. It ingests the hardware, the server capacity by itself. So, if users go from, let's say... 100 to 500, we don't see a dip in performance. It still behaves the same. Because of this new integration technology with the cloud, they are scalable in that regard.

We are in contact with technical support. One service we have is Tableau online. If we see a dip in performance, we raise a ticket to the Tableau support team, work with them and make certain they address our issues. I would rate my experience with them as three out of five. 

We used Tableau from the get go. 

While I was not directly involved in the setup, I know that it's not that easy. There is a need for a proper administrator who has experience in that field.

We used an integrator from Tableau when implementing.

Our experience was good and we were assisted with our implementation requirements. They were able to make notes to match our use case and answer all of our questions, including those concerning the number of users we have and how to set up the server.

I'm not part of the administrative group which handles the setup. I am mostly a consumer and responsible for building the desktop. I use the desktop version to build the dashboards and am not responsible for the server health check or maintenance. As such, I am not in a position to provide information about the staff required for maintenance, updates and checkups. There are a couple of people who are responsible for this, one from the customer side and another from our team. Both parties are in sync when undertaking these activities. 

I have no knowledge concerning the licensing costs of Tableau. 

The solution is mostly deployed on-premises, although we have also done cloud-based deployment. 

We have around 500-plus users making use of the solution and mostly 90 percent are viewers. We have very few creators or explorers. Creators comprise seven percent and explorers three percent. 

My advice to others would vary depending on their use cases, what they're looking for and the level of competency they have within their organization to use it. Tableau has a steep learning curve. So, it depends upon one's use case, the reason the person is going with that specific BI tool. The procurement department would need to evaluate the use cases very carefully, because there are so many BI tools available in the market. One's focus should be more on a centralized tool when bringing a new one to his organization. It should address all the answers to one's users, like what they're looking for. Definitely Tableau is good in the data discovery part and it can handle large data sets. So, all of these things should matter when one is trying to evaluate a tool.

I rate Tableau as a seven out of ten. This is because we are using it and it has a steep learning curve. It's not user-friendly. One must build a competency in creating the visualization and then support it. All of these things matter when one is evaluating a tool. That's why a shift is going towards Power BI.