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Tableau OverviewUNIXBusinessApplication

Tableau is the #1 ranked solution in our list of top Data Visualization tools. It is most often compared to Microsoft BI: Tableau vs Microsoft BI

What is Tableau?

Tableau helps people and organizations become more data-driven as the trusted leader in analytics.

The Tableau platform provides the breadth and depth of capabilities to serve the needs of even the largest global enterprises in a seamless, integrated experience. Tableau is designed to fit, not dictate your data strategy, and adapts to your environment with unmatched flexibility and choice, while meeting the toughest governance and security requirements.

People love using Tableau because it is both powerful and intuitive—and offers a fundamentally different user experience by empowering people of all skill levels to explore and analyze data using visuals and natural language. Tableau has become the standard language of analytics for modern business users and continues to lead the industry with the most passionate and engaged user community in analytics, a customer base with millions of users at more than 80,000 organizations, and a deep commitment to customer-focused innovation

Evaluation Guide: How to choose the right BI & analytics platform

Redefining the role of IT in modern BI world

Tableau is also known as Tableau Desktop, Tableau Server, Tableau Online.

Tableau Buyer's Guide

Download the Tableau Buyer's Guide including reviews and more. Updated: October 2021

Tableau Customers

Accenture, Adobe, Amazon.com, Bank of America, Charles Schwab Corp, Citigroup, Coca-Cola Company, Cornell University, Dell, Deloitte, Duke University, eBay, Exxon Mobil, Fannie Mae, Ferrari, French Red Cross, Goldman Sachs, Google, Government of Canada, HP, Intel, Johns Hopkins Hospital, Macy's, Merck, The New York Times, PayPal, Pfizer, US Army, US Air Force, Skype, and Walmart.

Tableau Video

Pricing Advice

What users are saying about Tableau pricing:
  • "At $70 per month, I think the price is a bit scary. I have a small consulting firm in Ghana, working in about 15 different African countries, and when it comes to our part of the world, $70 a month is a lot of money for software."
  • "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."
  • "Tableau has core-based and user-based licensing, and it is tied to scalability. The core-based licensing is about you buying a certain number of cores, and there is no restriction on the number of users who can use Tableau. The restriction is only on the number of cores. In user-based subscription licensing, there is a restriction on the number of users. Big companies and government organizations with a lot of users typically go for core-based licensing. User-based subscription licensing is a more common model. It has user roles such as creator, explorer, and viewer. A creator is someone who does the groundwork or development work. An explorer is someone who is into middle management but is not technically savvy, such as a category head. A viewer is like a typical decision-maker in senior management. For each role, Tableau is priced differently. The viewer role has the minimum price, and the creator role has the highest price. This pricing is available on their website. Everybody can see it."
  • "The pricing is $70 per month. You have to pay about $800 or something in that ballpark annually for one license."

Tableau Reviews

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YAWANTWI-ADJEI
Data Visualization Specialist at Data Catalyst
Real User
Top 5
Lets me train new users quickly, easily, and intuitively

Pros and Cons

  • "Tableau is easy to use. That's the first and most important thing. I not only provide consulting but I also train people to use it, so with its ease-of-use it's not as difficult for me to train executives and management staff, because they don't have the IT background, unlike when I'm using Python."
  • "Overall, the only major frustration that I have had so far is with Tableau Public. I first used Tableau Public when I was building capacity, and when there was a later release to download and you wanted to upgrade, all your work would have to be manually re-entered."

What is our primary use case?

In my consulting firm, I use Tableau for data visualization and data analysis. Alongside Tableau, I also use Python and, on occasion, SPSS.

The EU had recommended Tableau for use in some of the statistics offices in Africa, including government institutes in Ghana, and just last week I was using it to do a program for the Ministry of Monitoring and Evaluation. There, I used Tableau to convey selling points to buy Tableau, which is one example of the consulting work I do for clients. 

I also train others in visual analysis with the use of Tableau. This September, I trained 265 medical statisticians. Last week, I trained 13 staff from the Ministry of Monitoring and Evaluation. And soon, I'll be training another group of 20 people on Tableau.

How has it helped my organization?

Tableau is a good product for people like me who provide data analysis training because it makes my job far easier. It's a good product and very easy to use, making the introduction of key technologies extremely simple.

For instance, when you get data, and go in to analyze it, people ask, "This is numeric?" People start thinking about, "How do I get all these tools?" Tableau takes the data and automatically breaks it down into two dimensions and measures. That makes it easy for me when I'm doing training.

So what I would say to trainees is, "Don't worry about all these data types, when you are designing your questionnaire, because in Tableau it breaks them into two. And the measures are the ones that you are going to actually work on. You normally break them down by the dimensions." And that makes it simple for people to understand. Otherwise people don't know where to start when it comes to data analytics.

Tableau makes life very easy for not only myself but also for others, because you can quickly get into data analytics and visualization with it.

What is most valuable?

Tableau is easy to use. That's the first and most important thing. I not only provide consulting but I also train people to use it, so with its ease-of-use it's not as difficult for me to train executives and management staff, because they don't have the IT background, unlike when I'm using Python. They don't know anything about programming, so Python is more difficult.

Tableau is also, right from the outset, a self-service product. It's easy for anyone to understand and use. Some of the organizations that I introduce to Tableau are using the full-blown version, i.e. the commercial version, and they can very quickly start analyzing data with the use of the Ask Data feature, where you can simply drag and drop while querying for data with natural language processing. You type in English and it will pick the data and analyze it for you.

Those features are built into Tableau which makes getting started with data analysis very easy. And it's also got some pretty good built-in visualization tools. I would say Tableau is one of the best when it comes to self-service functionality.

What needs improvement?

I attended a Tableau conference recently, and a quick improvement came to mind. When I am training people how to use it, I've come across situations where I've found it difficult to explain relationships. For example, when you want to blend data or when you want to show relationships, like when linking multiple tables; well, if you're an IT guy, that's easy. But if you are not an IT guy, you don't know anything about entity relationships, and it becomes a bit difficult for others to follow along.

It takes me a long time to get people to understand, even up to the point where I feel that this is the lowest level that I can go in terms of explaining it. I realized that many people don't really have any experience or knowledge about relationships between objects, and it makes it hard for me to get my teaching across. 

So I was suspecting, and I think I made this recommendation, that Tableau could find an easier way to introduce relationships. For now, if you want to build relationships in Tableau, or even in Excel, you have things like Access modules and Sheets. But how do I know that I need to use one object with another for the relationship. And if you then put in a table, what do you do after that? You have to double click, but people don't know that you have to double click.

I was hoping that there's a way that they can make that process a bit easier, though I don't know how they will do it. Perhaps when you load Tableau and connect to a data source, there would be a prompt that asks you if you want to link two tables together. So if you want to link two tables together, maybe you do A, B, C, D.

That might help with the self-service idea. If you're talking about self-service, then it should be easy for people who do not have the time, or who do not have that IT background, to pick the data and use it correctly.

In addition, and more generally, what I would like to see more support for is predictive analytics. When you're doing descriptive analysis, Tableau is excellent, and it's easy to do. But when you are trying to predict something, like in Tableau's forecasting feature, it seems to require date fields, or it won't work.

But I can forecast something without relying on date fields; maybe I want to predict that a branch has to close if it doesn't want to make something soon. I don't need dates to do that. For this reason, I'm using Alteryx for predictive modeling instead of Tableau.

Overall, the only major frustration that I have had so far is with Tableau Public. I first used Tableau Public when I was building capacity, and when there was a later release to download and you wanted to upgrade, all your work would have to be manually re-entered. I don't know how they can solve that. I was expecting that they might make a release on this upgrade, and then I can hit upgrade and it will install over what ever I have already.

Otherwise, for now I think they are doing well and I know they're still adding a lot of features. But it does sometimes make our work difficult, for those of us who are building capacity, and who are regularly changing people around. It means you have to keep learning all the time.

Another small detail for improvement is that when you draw bar charts, the default color could be something more neutral like gray. Instead, the default is blue, and I don't exactly get why this is the case.

For how long have I used the solution?

I've been using Tableau for the past three years now.

How are customer service and technical support?

I contacted support when I had a problem with data entry in 2018 or 2019. I spoke to a man based in Ireland and he was super.

I had originally put the problem I had on the Tableau community support forum, but I didn't get the right answer. I've forgotten the exact problem but it involved connecting to a data set from an Excel file. Instead of the data field displaying the data for you, what I got instead was an error or no response.

It kept happening like that so I sent a message to support, who gave me some steps to follow. I followed them but it still did not work. However, I realized that any time I do it and it shows up and I click data,  it then suddenly goes off. I'm still wondering why that happened. I think it depends on the size of the file or some other reason. I have not tried it again because I'm a bit busy now but it's something that I want to go back to because support didn't give me a satisfactory answer.

They told me, "Do this." I said, "I tried it. It did not work." They asked me again to do something and I tried it, and it still did not work. But then I tried on my own, and this time when the problem came up I clicked the data interface twice to reload it. On the second time I clicked, it worked, but I don't think that is the right way to handle it. 

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

I used Power BI before discovering Tableau in 2016/2017.

At first I did not like Tableau, because Tableau initially put me off considering that I have a problem with how Françafrique countries, like in West Africa, are controlled by France to not buy anything from Anglophone countries. I've worked in 15 African countries. And for instance, in Ghana, we are bordered by Françafrique countries but they haven't bought things from here because France tells them, "Don't buy." Which to me is wrong. Why should you sit in Paris and dictate to Africans?

I also decided that, "Okay. I'm not going to go into any French country and work." So, for my consultancy, apart from mainly Côte d'Ivoire, I also said, "Look. It is the attitude towards Anglophone and West African countries, I'm not going to help anybody." Because my contract with the World Bank was to build capacity. So I decided I'm not going to go there.

So, when I saw Tableau first, the word itself made me think that this might be the same kind of product, and I would not even look at it, because I was against it.

I kept on using my Power BI until a colleague, another consultant who we met from South
Africa, said to me while I was demonstrating Power BI, "I think you can use Tableau." I said, "What is Tableau? I don't want it." He said, "Oh I don't know much about Tableau, but somebody told me it's easier to use than Power BI." He said, "Why don't you look at that?"

We were working on the same project and I told him, "No, I'm not interested, I will not
look at it. It's a strange product, I don't want to look at a different product." And the guy insisted, "Oh please, you must take a look at it." Because we were looking at the project like we're a team, I said, "Okay, I'll look at it."

So that evening I downloaded it and I realized that all the things that I'm doing in Power
BI, that requires some level of IT background, well, I don't need that in Tableau. So then I decided, okay, let me really look at it. Who is behind Tableau? I asked where is the name Tableau from? Where did you get that name from? Okay.

So that was the time I changed my mind towards Tableau, and to be honest with you I've not regretted anything for doing it. I'm quite happy about it.

How was the initial setup?

Setup is not that difficult for me. However, I remember in Gambia, there was some initial difficulty when I was teaching how to set up the organigram for the National Social Staff System.

In the National Social Staff System, you have about 11 ministries involved and the coordinator, and it's the coordinating agencies in Bureau of Statistics. So I needed to set up the system so that all the other ministries can enter their data. And when you enter the data, the other ministry, let's say, Ministry A can also enter data. And Ministry B cannot see what Ministry A is doing.

Now, when I was doing it, it was not difficult at all, but because I had to handle other systems and leave, I tried to explain it to them but they found it a bit hard to grasp.

So where you have multiple alliances and you set them up like organizations, it can get a bit complex. Because there's differences within the same organization under different departments. It's not a big problem when you buy Tableau for one single organization, but when you set things up for multiple organizations like the National Social Staff System, it can get problematic.

The national system is made up of different entities: Ministry of Health, Ministry of Agriculture, Ministry of Finance, etc. They are different ministries and they don't necessarily need access to all of each other's data. But if you buy Tableau for each of them then that is fine but if it comes to a situation where they all come under one number and you're setting up, you don't want one ministry to see what the other is entering.

So there was definitely a bit of a problem there. But I can't blame Tableau because no matter what it is, sometimes you need a certain level of IT skills to get certain things done. 

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

At $70 per month, I think the price is a bit scary. I have a small consulting firm in Ghana, working in about 15 different African countries, and when it comes to our part of the world, $70 a month is a lot of money for software.

In fact, where Tableau was approved for use in Gambia, I had the EU pay for three years. But I know it's expiring soon, and I don't think they will have the money to renew. I don't know how they're going to do it. When you come to Africa, especially when you're on the net, we don't use it so much, so I don't know if there is something that they can do about pricing for people in the African continent.

Yet recently, I trained 265 medical statisticians on how to visualize their data, using Tableau Public. They were so happy. And they thought, "Oh, this is very easy for us to do." But when they asked me about the price and I told them, they said, "$70? But we can't pay."

So that for me is a problem here. And, mostly, it's a problem for everybody. There are some companies that can easily afford it, but the majority of companies cannot.

Which other solutions did I evaluate?

I have occasionally used IBM SPSS for similar work that I perform in Tableau, but I only use it when the client absolutely requires it.

What other advice do I have?

I wouldn't tell people to go with Tableau just because it's the tool that I use. I would instead emphasize its remarkable ease-of-use and the way Tableau really listens to their users and comes up with frequent upgrades. 

I would rate Tableau a nine out of ten. 

Which deployment model are you using for this solution?

On-premises
Disclosure: My company has a business relationship with this vendor other than being a customer: Integrator
JW
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.
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Learn what your peers think about Tableau. Get advice and tips from experienced pros sharing their opinions. Updated: October 2021.
542,721 professionals have used our research since 2012.
ITCS user
Manager, BI & Analytics at a consultancy with 11-50 employees
Real User
Top 5Leaderboard
The visualizations bring out patterns buried under a mountain of data. The tool offers unparalleled flexibility in terms of the types of visualisation that one can create.

What is our primary use case?

I've used Tableau primarily to visualize data on asset performance. These visualizations pertain to reliability engineering and I've created charts and dashboards showing key performance indicators such as mean time between failure for different asset components, trend/pattern of asset behavior (different types of events occurred in the asset) prior to failure and asset grouping based on their health and performance.

Tableau is so flexible as to enable the user to show events that have occurred over the entire lifespan of each asset. Normally, this requires a bit of data-wrangling but in my experience this graphic has found a lot of favor with multiple clients.

All of these visualizations were created in a local environment (at the desktop-level) using data from .xlsx and .csv files.

How has it helped my organization?

In our line of work, we primarily use Tableau Desktop/Server to visualize data based on our clients’ requirements. Once, while dealing with a procurement scenario, we found that the client could save $2.00 on each unit of Part A if they ordered it from Supplier X rather than from Supplier Y.

In another case, we designed dashboards that showed data from different sensors located throughout a building. This kind of an application could enable stakeholders to monitor building climatic conditions in real time and adjust thermostats according to CO2 levels and occupancy, thereby driving efficient consumption of power.

In this way, Tableau visualizations can be used to take more intelligent decisions as they bring out patterns buried under a mountain of data.

What is most valuable?

I believe the most valuable feature of Tableau is the flexibility it offers with regard to the types of visualizations the user can create. A lot of other products in this space offer limited chart types and work in a way that provide little room for customization, if any. But Tableau allows the user to work with its predefined templates such that the end result can be a visualization that is highly customized - in terms of the design, colors, sizes, shapes and the overall visual appeal. This is an invaluable feature as it enables one to communicate more powerfully from the data.

I would also consider the ‘Create Calculated Field’ feature as very valuable. It’s one that I’ve used quite extensively. Most of the time, the data we work with will not have all the necessary features that enable us to tell a good, convincing story out of it. Therefore, it becomes imperative that we create them and extract the maximum amount of information possible from the data.

Formatting charts - colors, lines etc. - is also simple and there are a lot of options for customization.

What needs improvement?

I would like to see the inclusion of a template to create a speedometer chart. I can understand that Tableau doesn’t have it as one of its default chart types because it’s not a good way to represent the data. Indeed that’s true, but speedometers are quite popular and once we had a client who was insistent on having highly-customizable speedometers and I had to spend a good amount of time to create them via multiple workarounds. In my experience, I've seen many customers who do not want to consider alternatives to speedometers.

I’ll address these two points:

  • Speedometers/dial charts are a not-so-good way to represent data
  • I had to resort to multiple workarounds to create a speedometer in Tableau

First, I’ll give you a few reasons as to why speedometers are not considered to be a good way to visualize data:

  1. Low data-ink ratio: ‘Data’ here refers to the data that you want to show on your chart/graph and ‘ink’ refers to the aesthetic elements of the chart such as lines, colors, indicators or any other designs. A low data-ink ratio implies that the quantity of ‘ink’ on the chart is very high relative to the small quantity of ‘data’ that is present on the chart. What does a speedometer or a dial chart do? It shows you the current state (value) of any system. Therefore, the data shown by the chart is just one number. Let’s come to the ‘ink’ part. Needless to say, there is a lot of ‘ink’ on a speedometer chart – so many numbers all around the dial, the dial itself, a needle that points to the actual number etc. The fundamental principle of data visualization is to communicate information in the simplest way possible, without complicating things. Therefore, best practices in data visualization are aimed at reducing visual clutter because this will ensure that the viewer gets the message – the right message – quickly, without being distracted or confused by unnecessary elements.
  2. Make perception difficult: The human brain compares lines better than it does angles – information in a linear structure is perceived more easily and quickly than that in a radial one.Let's say I’m showing multiple gauges on the same screen. What's the purpose of visualizing data? It's to enable the user to derive insights - insights upon which decisions can be taken. The more accurate the insights, the better the decisions. So, its best that the visualization does everything that helps the user understand it in the easiest possible way. Hence, the recommended alternative to a dial chart is a bullet chart
  3. Occupy more space: Assume that there are 4 key process indicators (KPIs) that I need to show on screen and the user needs to know whether each KPI is above or below a pre-specified target. If I were to use dial charts I’ll be creating 4 dials – one for each KPI. On the other hand, if I were to use bullets, I’ll be creating just one chart where the 4 KPIs will be listed one below the other and each one in addition to showing its actual and target values, will also show by how much the actual exceeds/falls short of the target in a linear fashion. As real estate on user interfaces is at a premium, believe me, this is definitely better.

Now, let me come to my situation where my client would not accept anything but a speedometer. As I’ve mentioned in the review, Tableau doesn’t provide a speedometer template by default. So when I was going through forums on the Internet I saw that people usually used an image of a speedometer and put their data on top of that image and thereby creating speedometers in Tableau.

This would not have worked in my case because my client wanted to show different bands (red, yellow and green) and the number of bands and bandwidths varied within and between dials. For example, one dial would have 2 red bands (one between 0 and 10 and the other between 90 and 100), 1 yellow band and 1 green band while another would have just one yellow band between 40 and 50 and no red or green bands. Also, these bands and bandwidths would be changed every month and the client needed to be able to do this on their own. Therefore, using a static background image of a dial was out of the question.

So, here’s what I did: I created an Excel spreadsheet (let’s call it data 1; used as one of the 2 data sources for the dial) in which the user would be able to define the bands and bandwidths. The spreadsheet had a list of numbers from one to hundred and against each number, the user could specify the band (red/green/yellow) in which it falls. The other data source (data 2) was an Excel sheet containing the numbers to be indicated on the dials. Then, in Tableau, I created a chart which had 2 pies – one on top of the other. Both the pies had numbers from 1 to 100 along the border, providing the skeleton for the dial. The top pie used data 1 and had the red, yellow and green bands spanning the numbers from 1 to 100. I then created a calculated field having an ‘if’ condition: if the number in data 2 matched the number in data 1, the field would have a value ‘yes’. Otherwise, it would have a value ‘no’. This will produce only 1 ‘yes’ and 99 ‘no’s’ because there will be only 1 true match. I put this calculated field onto the ‘Color’ shelf and chose black for ‘yes’ and white for ‘no’ – this formed the content of the bottom pie. So the bottom pie had 99 white colored slices (which looked like one huge slice) and just 1 black slice (which looked like a needle). I made the top pie containing the red, yellow & green bands more transparent and this gave the appearance of a needle pointing to the KPI value, also indicating into which band the number fell, thereby enabling the client to gauge their performance.

For how long have I used the solution?

One to three years.

How are customer service and technical support?

I've not directly contacted the tech support team of Tableau Software myself but whenever any clarification was required regarding the creation of a particular visualization, I've found many discussion forums and blogs, the contents of which have been extremely helpful.

Which other solutions did I evaluate?

I have also worked with Microsoft's Power BI and I've found Tableau to be far more flexible and user-friendly in terms of the variety of visualizations it allows you to create.

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.
Jerry Paul
Product Consultant at a tech services company with 201-500 employees
Real User
The best analytics platform with great visual capabilities, best stability, and rapid enhancements

Pros and Cons

  • "Our customers love the visual capabilities on top of it and the ability to explain and get the required data. There is no other product like Tableau in the business intelligence and analytics space."
  • "Tableau is an end-to-end analytics platform, and it is doing a pretty good job in terms of connecting to the data and analyzing it. It can, however, do better in terms of data management and the ETL features, which are not on the advanced analytics or machine learning side. Tableau Prep is where users would want to see more advancements. They can improve Tableau Prep, which is an analytic platform tool for data cleansing. People who work with data spend most of their time curating the data. Cleaning up the data and getting it ready for analysis is what takes the most time. If Tableau can invest more time in improving the Tableau Prep platform, it would be great. Previously, Tableau didn't have the functionality for writing to a database. So, you couldn't really alter the database tables and write to your database, but they fixed that in one of the very recent releases. However, it isn't really advanced and should be improved."

What is our primary use case?

We are into the distribution of licenses, and we also have a services arm that takes care of the implementation.

Our customers use it for different use cases, such as fleet management, HR analytics, and retail analytics. They also use it for forecasting and predictive modeling. In the EMEA region, the analytics market isn't very mature. Therefore, many customers just restrict themselves to basic statistics in Tableau. At the most, they go for the predictive functionality, which is inbuilt in Tableau.

Its deployment depends on the use case. Some customers use it on the cloud, which is Tableau Online, and some of them go for Tableau Server, which is on-premises.

What is most valuable?

Our customers love the visual capabilities on top of it and the ability to explain and get the required data. There is no other product like Tableau in the business intelligence and analytics space.

What needs improvement?

Tableau is an end-to-end analytics platform, and it is doing a pretty good job in terms of connecting to the data and analyzing it. It can, however, do better in terms of data management and the ETL features, which are not on the advanced analytics or machine learning side. Tableau Prep is where users would want to see more advancements. They can improve Tableau Prep, which is an analytic platform tool for data cleansing. People who work with data spend most of their time curating the data. Cleaning up the data and getting it ready for analysis is what takes the most time. If Tableau can invest more time in improving the Tableau Prep platform, it would be great. 

Previously, Tableau didn't have the functionality for writing to a database. So, you couldn't really alter the database tables and write to your database, but they fixed that in one of the very recent releases. However, it isn't really advanced and should be improved.

For how long have I used the solution?

I have been using Tableau for three years.

What do I think about the stability of the solution?

With respect to stability as a performance-driven metric, it is wonderful. Tableau is being used by one of the biggest gaming companies. Stability has mostly got to do with:

  • Connectivity to your different data and database platforms
  • The amount of data that you're dealing with

The Tableau platform can handle both of these because there is no limit per se in terms of the data size. However, a big fee is a challenge for everybody, and there is no escape from it. 

Tableau has recently acquired Hyper, which speeds up the performance. Hyper is also something that Facebook uses. Therefore, when it comes to stability, it is one of the best solutions in the market. You don't need to worry about it. 

If there are some glitches because a huge amount of data is coming in, there is an inbuilt performance monitoring option in Tableau where it actively monitors every user click on the platform. It will show you the results on the fly and tell you the part of your dashboarding or activity that is consuming the most memory. This way, you can optimize its performance.

What do I think about the scalability of the solution?

It is scalable. The beauty of this product is that it is for everyone. Tableau is a good fit for small enterprises to large enterprises. It can also be used in small departments of a company. The mission of Tableau is to help people see and understand data. So, it is not only for the IT people who understand the technicality of it. It is end-user-centric, and therefore, everybody can use it. It can be used by the marketing, finance, credit, and sales departments. The developers, data scientists, statisticians, and other people can also use it. It is for everyone. 

You can scale it vertically or horizontally, or you can go both ways. You can have a single node configuration and add more RAM or more memory to the same node, or you can have a multi-node configuration. Both are supported. You can add nodes depending on the number of users who want to consume the analytics.

How are customer service and technical support?

I am not completely aware of it because I mostly handle pre-sales, but I do know that you can raise a support ticket with Tableau very easily. They have 24/7 support, and the priority of your use case depends on the agreement or the contract that you have with Tableau. There is Tier 1, 2, and 3 support.

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

I have used SQL on different platforms. I have also worked on Python and R to generate plots. I can't stress enough on the fact that as compared to other solutions, Tableau is much easier, clearer, and more intuitive while using your data. You can actually see every bit of your data. They are able to achieve their mission and help people see and understand data. 

How was the initial setup?

Its initial setup is very easy because Tableau has a new graphical user interface, and there is no need for you to script or code your installation process. It only takes a day to set up everything, and it does most of the configuration on its own. It is a very easy process.

In terms of maintenance, there are product upgrades that get released every quarter. It has quarterly upgrades and updates because it is enhanced so rapidly. They spend 25% of their annual revenue on R&D. They have constant interaction with its broad community, and they constantly take in user feedback. If there is a maintenance requirement or some issue with the product, most of the time, it automatically gets resolved in the next upgrade.

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

Tableau has core-based and user-based licensing, and it is tied to scalability. The core-based licensing is about you buying a certain number of cores, and there is no restriction on the number of users who can use Tableau. The restriction is only on the number of cores. In user-based subscription licensing, there is a restriction on the number of users. Big companies and government organizations with a lot of users typically go for core-based licensing.

User-based subscription licensing is a more common model. It has user roles such as creator, explorer, and viewer. A creator is someone who does the groundwork or development work. An explorer is someone who is into middle management but is not technically savvy, such as a category head. A viewer is like a typical decision-maker in senior management. For each role, Tableau is priced differently. The viewer role has the minimum price, and the creator role has the highest price. This pricing is available on their website. Everybody can see it.

What other advice do I have?

I would advise checking your minimum configuration. There is a specific hardware configuration that you need before installing the software, which varies based on your development, test, and production. You should also decide on whether you need Tableau Online or Tableau Server. Tableau Online supports most of Tableau Server functionalities, but there are some limitations for certain data connections and refreshes. This is something that you need to be aware of while choosing between Tableau Online and Tableau Server.

Sometimes, organizations that can spend or have a good budget just go for Tableau Online because they don't have to worry about maintenance and upgrades. You're already on the latest version, and everything is taken care of by Tableau. The trade-off is that sometimes you may not have your refreshes and connectivity in the widest section possible, which is something that you can do with Tableau Server, but it happens only in rare cases.

It is the best product at the moment. If you look at Gartner's report for BI and analytics, Tableau has been the leader for nine years in a row, which is a very big achievement. There is nothing else like it. You will see Microsoft above Tableau, but Microsoft provides a product suite, whereas Tableau is just BI and analytics. It is not an apple to apple comparison. 

I would rate Tableau a nine out of ten.

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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Sreekrishna Mohandas
Chief SAP - ICT (Digital & IT) at a energy/utilities company with 1,001-5,000 employees
Real User
Top 20
Great for following KPIs, good performance and good for presentations

Pros and Cons

  • "The solution makes for very productive and really informative decision making. It can lead the whole business and build a strategy across whole working departments."
  • "The cost of owning the solutions from Tableau is much higher compared to any other analytical solutions."

What is our primary use case?

We have been using Tableau for all sorts of analytical tasks. When I was having an ERP SAP practice, we used SAP analytical tools and IBM Cognos plus Tableau for dynamic display session purposes. Tableau ended up being the best solution. That is why we moved over to Tableau. We predominantly implement and use Tableau. 

How has it helped my organization?

It's a pure data platform. Everyone relies on Tableau. Our departmental meetings and reports for monthly meetings and reviews happen live on Tableau. We can prepare all of our KPIs on it. In fact, all of our KPIs can be placed onto one single screen and divided into nine tiles that can be further divided.

We can easily review and define all of our KPIs. The data is perfectly validated. It allows us to run corporate and board presentations purely on Tableau's visualization center.

What is most valuable?

It's an extremely good product with respect to performance and analytics. 

All the transactions that are happening are happening in SAP and some of the solutions are in Oracle as well. The combination, the data extraction which is filtered into authenticated, validated financial data, sales data, material data, etc, into Tableau platform is very useful for us.   

The solution makes for very productive and really informative decision making. It can lead the whole business and build a strategy across whole working departments.

What needs improvement?

The licensing costs of Tableau are on the higher side and probably if you wanted more adaptability in usage across business divisions you need to have more reasonable pricing of licenses of Tableau. Tableau is a standalone product. That is a disadvantage.

Due to the fact that it is a standalone product, it has to extract the data from other ERP systems or other bespoke systems and other data systems, etc. If you have big data systems and you have got other informed decision-making tools and the data is being extracted into Tableau it is dependent on many other platforms.

In contrast, if you use SAP vertical data systems and you have SAP's Data Hub, etc., then everything is vertically integrated. The whole data pipeline is vertically integrated and there is a visualization screen right there as well. Therefore, you don't normally have to go for a separate integration process altogether or need a data extraction solution.

In the end, Tableau has got two or three disadvantages in the sense that it is not a seamlessly integrated platform, end-to-end platform. It's purely a standalone reporting tool. On top of that, the licensing cost is extremely on the higher side. Thirdly, IT divisions probably are a little bit hesitant to use Tableau due to the fact that separate training is required, and separate skill sets are needed to develop everything. 

The cost of owning the solutions from Tableau is much higher compared to any other analytical solutions.

For how long have I used the solution?

We've used Tableau for the past two and a half years or so.

How are customer service and technical support?

Technical support is okay. It depends on the countries. I was in Australia for some time and there the support is much better than in India. This is probably due to the fact that a number of users are struggling with it and you get delayed support here. It's better to use Tableau proactively and develop a center of excellence in our organization. That is what I did and it helped us out a lot. I don't have any complaints about technical support per se.

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

Tableau is undisputedly the number one analytical product in the world. I have given a long presentation to management and the CEO about what differentiates Tableau over other products such as Cognos and Hyperion, SAP, etc. Lumira also is a strong contender, however, Tableau is way ahead because of the dynamic reporting that is possible and the whole virtualization that is very easy to produce, or reproduce. The business users themselves enjoy working on Tableau much better than other solutions like SAP, Cognos, Hyperion, etc.

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

The pricing of the solution is a bit high.

What other advice do I have?

We're only customers. We don't have a business relationship with the company.

We have not moved to the cloud so far with this product. Only SAP Ariba is on the cloud. The rest of our solutions, all analytical solutions, are on-premise solutions only.

Businesses should know what exactly they can do with Tableau. It's not just a visualization center or dashboard. You can contact a lot of assets that are in use - such as institutional analytics, predictive analytics, and prescriptive analytics. It can integrate with any artificial intelligence learning solutions and analytic solutions. That is where big data analytics play an important role. Modern business is more focused on all sorts of big database analytical solutions, especially for retail and other larger CRM business.

A company needs to decide answers to questions such as "how do you extract data?" or "Which department wants what data?". They would definitely need to have an initial, extremely focused approach of implementing it, with the full participation of the business teams. That is how a successful Tableau implementation needs to happen. However, it doesn't end there. You also need to educate business users or corporates on the solution as well.

Tableau is an extremely good product. I'd advise other users to use all aspects of and take advantage of its capabilities. Tableau has many licensing products available and a whole analytical model should be under one platform rather than going for bits and pieces from Oracle, IBM, SAP, Microsoft, etc.  Tableau is undisputedly the leader of the whole analytical solution and it should remain so only because it should have a larger use phase.

The training of Tableau is good, however, users should be aware that the consultants' availability across various countries is limited. I'm from Bangalore and if I need a Tableau consultant it's very difficult to locate one. You can, however, often find freelancing consultants. They can also get the job done.

Overall, I'd rate the solution seven out of ten.

There are so many solutions on the market. Primavera solution is a project management software. There is no product that can beat Primavera in the project management functions so you have many such project management products, SAP Project Manager, Product and Portfolio management is there, Microsoft Project is there. There are other Oracle project management solutions out there and then Primavera is there. 

When Oracle purchased this solution, the popularity of Primavera died out. I've personally stopped recommending that particular product. There are others that cost less, so why use that one?

Tableau should learn from Primavera, and ensure it builds its user base and market its abilities so that corporates understand the depth and breadth of its usage. Many only use 10-20% of its capabilities. It's the duty of Tableau to ensure potential use cases are advertised and more information is disseminated to corporates to help them understand how it can benefit them and why that should adopt it.

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.
Djalma Gomes, Pmp, Mba
Managing Partner at Data Pine
Vendor
Top 5
Data analysis that is easy to use, straightforward and flexible

Pros and Cons

  • "Tableau has improved my organization in a variety of ways, one of its uses being that of data analysis. A feature I have found most valuable is the ease of use and straightforwardness, in addition to the flexibility of Tableau."
  • "An area needing improvement involves the complexity of the product should you need to alter a lot of parameters. If you have technical servers, much interface, different providers and more serious processes, that will be time consuming."

How has it helped my organization?

Tableau has improved my organization in a variety of ways, one of its uses being that of data analysis. It provides a server platform for sharing information. We use it for internal collaboration, as well as other tools for data catalog, for creating the dashboards, for preparing the data in preparation of creating the dashboards, called an ETL extract, and as a tool to transform and load. Tableau is a platform that has several products, perhaps four or five, that average for the fifteen of big data, data evaluation and data collaboration. No specific aspect can be used for this and it can be employed in marketing and finance. It serves the needs of data analysis and providing an algorithm for machine learning. For instance, you can have a logistic regression to analyze whether a specific customer is a good bet or not, such as a bank that is contemplating the loan of money. It allows you to visualize and analyze your data no matter what it may be, though it can be used for an alternate solution.

What is most valuable?

A feature I have found most valuable is the ease of use and straightforwardness, in addition to the flexibility of Tableau. I like the fact that Tableau can connect to a wide variety of databases, be on cloud or on-premise. Tableau can connect to over 100 database types, including structured and non-structured databases. Tableau can connect to a PDF and extract all the tables you have in that PDF. Suppose you have a one hundred-page PDF containing sixteen tables of data. Tableau can connect to that PDF and extract its data. Tableau can connect to Google Drive, to a host of marketing portals on the internet, to cloud companies such as AWS or Alibaba and to many different types of databases. That's one huge advantage of the tool.

While it can be complex if you need to alter a lot of parameters, it provides simple installation. It is very easy. All you would need to do if you have only one Tableau running server is to employ the maximum connection and install a license column in Adobe Reader. 

What needs improvement?

An area needing improvement involves the complexity of the product should you need to alter a lot of parameters. 

Definitely speaking, it's straightforward and it's very easy. Implementation problems can be dealt with by the client, in place of the user consultant. Let me give you some examples of things that could take long in a Tableau implementation. Suppose you have five different business areas in your company: marketing, supply chain, finance, HR and procurement. Let us suppose that access to HR salaries is not company-wide but is limited to only a select number of people in HR, such as the manager or the director of the department. Yet, I want people in the supply chain to be able to see and access different data from different areas. While this would not be technically difficult it would be time consuming if the businesses are very particular. There may be many policies involved in access authorization, in data availability and the like.

This can involve a very strict security process using an outside identity provider. Instead of just logging in your username and password, you may have different technologies which are more safe and secure that need different providers to interface in Tableau. Depending on the need, this will be time consuming. For instance, while I don't know how this would be in your country, suppose you have an identity provider, in Brazil, marketing in Tableau. If you go to Asia, you may sometimes have a bio-metric identity that your hand or fingers employ which is going to get back at you. In that circumstance, they are going to send you a number or a code in your cellphone, requiring two steps, one to enter the bank and the other to withdraw your money. So, these things we call an outside identity provider, meaning a different vendor or different companies who manage the servers of managing identities. These would entail an integration with Tableau and these outside companies for security purposes. This would involve them sending me files and me sending them back in order to authenticate the user into the Tableau server.

This can be time-consuming because they involve or require a different partner. Tableau is made for basic needs, such as requiring a user and a password to log in to the server; an unsophisticated architecture; or use of a single instead of a cluster of servers. If you have non-specific data security needs or you just want to analyze and sell data, that can take less than a day. But if you have technical servers, many interfaces, different providers and more serious processes, that will be time consuming. 

While Tableau does integrate with Arc server and Python server, the integration process is slow and the information is integrated in a protracted fashion. Sometimes your data will vary. You may have a vector of data. You may have a matrix of data. For some algorithms we do not use regular data, but a different data structure. Tableau does not work with these different data structures. As such, interfacing with Arc server and Python server, which are still languages that are widely used in machine learning, all happen slowly. It does not happen by a matrix of data and data vector. 

For how long have I used the solution?

I have been using this solution for five years. 

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

In the past I worked with Oracle E-Business Suite while working with ERP markets over a thirteen or fifteen year period. Yet for the past five years I've been focusing mainly on artificial intelligence, machine learning, big data and the use of other software, such as  Tableau and Azure for the purpose of developing and building data to create algorithms and visual dashboards to show the data. It's been around five years since I have turned my focus solely to big data and machine learning. 

How was the initial setup?

Definitely speaking, the initial setup was straightforward and very easy. 

Which other solutions did I evaluate?

Another option I evaluated is Power BI from Microsoft. It's cheaper than other solutions and requires fewer different packages. The major competitor of Tableau is Power BI from Microsoft and Microsoft's much cheaper than Tableau. But Microsoft usually requires me to be on Microsoft cloud Azure. You have to buy other solutions for an integrated solution. At the end your cost will be much higher. So Tableau is more flexible. 

In Tableau, I can have a scatter plot with millions of marks. Suppose I have a graph that plots my value against my process and each dot in the graph is a sale that I've made. So I have 30 million dots in this graph reflecting my 30 million sales. Tableau can run this easily and fast. Power BI cannot. Power BI has a limitation of 13,500 marks, meaning Tableau has more capacity in delivering data than its competitors. 

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Tariq Raza (MS Certified)
Operations & BI Analyst at American Hospital Dubai
Real User
Top 5
Easy to use with good drag-and-drop functionality and very stable

Pros and Cons

  • "It's very easy to set everything up."
  • "There's no mature ETL tool in Tableau, which is quite a negative for them."

What is our primary use case?

We primarily use the solution for our data visualization, our different types of data. It is linked to our normal data visualization. It's not usually related to the medical side of the business. However, it is related to the revenue, and financial accounting, and submission on the RCM side. 

What is most valuable?

If I compare Tableau with Power BI, I prefer Tableau. It's easier to use.

The solution has very good drag-and-drop functionality and the screens are easy to navigate. You can easily create measures and dimensions. It has a user-friendly layout that makes task completion simple. In comparison, in Power BI, all of these actions are quite cumbersome.

It is quite similar to Excel. If a person has good Excel knowledge, it will be quite intuitive to learn.

Tableau is the whole package.

The solution allows you to write in SQL and Python. We don't need to write the Python code and we don't need to write the SQL script. However, it is an option that's on the table.

The solution is very stable.

You can scale the solution well.

It's very easy to set everything up.

What needs improvement?

There is another ETL tool for Tableau that is new. It takes time to reach some level of experience. IN Power BI, they have Power Query. I find it easier to convert the information in Power Query with a single shortcut key. That's not an option in Tableau. 

You have to prepare your data. It will take a lot of time to clean the data. 

There's no mature ETL tool in Tableau, which is quite a negative for them. They need to offer some built-in ETL tool that has a nice and easy drag-and-drop functionality.

There needs to be a bit more integration capability.

For how long have I used the solution?

I've used the solution for about six months to one year. It wasn't very long. I used it at my previous organization. We're also using it at my current company. At this organization, we've only had it for about three or so months. It's quite new here. 

What do I think about the stability of the solution?

The solution is extremely stable. It's much more stable than, for example, Power BI. There are no bugs or glitches. It doesn't crash or freeze. It's very reliable. The performance is great. We've never faced any stability issues while using the product.

What do I think about the scalability of the solution?

I'm not sure how many users we actually have within the company. 

Tableau is one package and there isn't too much complexity. The main pieces are Tableau itself, Prep Builder and Tableau Server, and Tableau Mobile. Sorry, Tableau Online. These four are the most basic software pieces of Tableau.

Whenever you purchase Tableau, you will pay a bit more and more. You will have access to the four main software products. After this, there is no need to purchase something extra. Therefore, in Tableau, there is no scalability issue. In comparison, if you will to Microsoft, there is a lot of products - such as Power BI. There is Power Automate RPA and Power Apps and MicroPower Apps also. You will need to call to Microsoft and they will integrate this Power App with your account. It takes time. With Tableau, there isn't an issue like that. 

How are customer service and technical support?

We haven't had any sort of technical issues. They did assist us a bit at the outset. and they were very good. They are always online and easily approachable. We're quite satisfied with their level of service.

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

We also use Power BI.

How was the initial setup?

The initial setup was very simple. It's not a complex process.

They have an excellent team here over at Tableau. They assisted us. 

The setup wasn't too difficult due to the fact that our system is not very complex. We work with rather simple data, which helped save us from suffering through many complexities. 

Maintenance is required at our database level. Our database is smart and lean, and therefore it's pretty straightforward. However long it takes for maintenance tasks is based on the level of data and on the heaviness. We basically do a sort of troubleshooting and some fine-tuning at the database level.

At the time of making visualization, we have to do some research to load everything properly on Tableau and have a refresh rate we can maintain. There should not be too much of a refresh rate every time. 

What about the implementation team?

We had Tableau's technical team help us here and there. They were great and we were satisfied with their help.

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

The pricing is $70 per month. You have to pay about $800 or something in that ballpark annually for one license.

What other advice do I have?

We are a customer and an end-user.

We are currently using the latest version of the solution.

I would recommend the solution. If a company really wants to go for some easy solutions, and something that is robust and dynamic this is a great option. Microsoft's Power BI also has its advantages and could be a good option as well, depending on what a company needs. If Mircosoft offered a bit more, we might even consider switching over. However, for us, Tableau is the better option. 

I'm using Microsoft Power BI also. Therefore, personally, I see the importance of the ETL tool. Microsoft is also adding many items rapidly - with new features two or three times a month. Tableau isn't making such advances regularly. 

Many people are considering shifting from Tableau to Microsoft very seriously. Therefore, Tableau needs to begin to compete. They need to offer more integrations and invest in a robust and easy ETL solution. It would really assist in cleaning the data.

If a company wants to onboard Tableau, they need to have some sort of ETL tool on the side as well. If they don't, and they don't have SQL or Python, I'd actually direct them to Power BI - simply to get that ETL capability. However, if the data is ready, and no ETL is required, Tableau is an excellent solution. If you just need to visualize the data, Tableau is the best.

Overall, due to the lack of ETL, and the inability to effectively clean the data, I would rate the solution at a six out of ten.

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.
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RP
Manager BI/Analytics and Data Management at a healthcare company with 10,001+ employees
Real User
Top 20
A stable solution which provides good visualizations, but the architecture should be improved to better handle the data

Pros and Cons

  • "The most valuable features are the visualizations, the way they show the combination charts."
  • "The architecture should be improved to better handle the data."

What is our primary use case?

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.

How has it helped my organization?

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. 

What is most valuable?

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.

What needs improvement?

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.

For how long have I used the solution?

We have been working with Tableau for almost seven years.

What do I think about the stability of the solution?

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.

What do I think about the scalability of the solution?

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.

How are customer service and technical support?

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. 

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

We used Tableau from the get go. 

How was the initial setup?

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.

What about the implementation team?

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. 

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

I have no knowledge concerning the licensing costs of Tableau. 

What other advice do I have?

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.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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