Tableau Enterprise Reviews

We use the solution to allow management the ability to create dashboards for our data center.

The solution is easy to use, flexible, our clients enjoy seeing the data on maps, and you do not need to be an expert in SQL to use it.

There could be improvements on the mobile application, it is lacking features. 

I have been using the solution for approximately one year.

I have found the solution to be stable.

The scalability is good, we have 100 users using the solution in my organization.

I am not satisfied at all with the support response, it takes a lot of time. Some tickets will take more than 10 days to have an answer, this is not helpful. There is some documentation that is very useful on their site. This is the worst support I have experienced, the support could definitely be faster.

We were using Qlik Sense before this solution.

The installation is straightforward. The time it took for the installation was approximately four hours. However, the configuration takes a lot longer but it is not a problem with this solution it is common for configurations to take a while.

We did the deployment ourselves. We have a team of two administrators doing the maintenance for the solution and a team of four for the development of the dashboard. 

There is a license required, we pay an annual license which is priced fair.

I recommend this solution to others. We are satisfied with the solution and are going to keep using it in the future.

I rate Tableau an eight out of ten.

We are consultants and implement this solution for many of our clients. We had a project for a telecommunications company, where we extracted the transaction data and helped them to find some trends and improve analytics. They were able to gain knowledge from the data and to see some KPI indicators and build some dashboards for commercial, risk and financial purposes. We help clients connect their raw data, prepare and clean, and generally carry out the cycle. We then help them to extract insights, trends and work on forecasting so they can visualize their indicators in dashboards or in some ad hoc analysis. I'm the general manager and we are partners with Tableau.

The solution has several platforms or tools to visualize data and to build dashboards. The Tableau Prep tool is great for data preparation and this is the most valuable tool for preparing data, cleaning and building data models or data warehouses. The main issue, and most companies have the same problem, is updating data, which they can do with Tableau Server, where you can synchronize data to automatically refresh daily, weekly or monthly. It means your dashboards and KPIs will be updated. Most people know Tableau because you can build beautiful dashboards, but the main beneficial features are behind the scenes.

The product could be improved with more features in data analytics. Tableau is not currently a good database for handling built-in models for data science in order to test, train and run the models. It's not currently an AI tool or a tool for machine learning. Right now it's more for non-expert users. If they could improve their analytical capabilities for data science tasks, it would be a better product. In order to carry out data science tasks now, we have to use Vertica for big data projects to discover and run machine learning models. It would be very good if they had their own machine learning capabilities built in. I'd like to see more features in data analytics, AI and machine learning capabilities.

I've been using this solution for the past 12 years.

The stability is good, we haven't had many bugs. They provide many updates every week and we don't have problems with Tableau in general.

The solution is scalable, we have around 15% of our clients that are large scale businesses with the majority being small companies. We provide support for our customers.

Two or three years ago, technical support was very good. I think that now there are many more users of Tableau, the technical support is not as good as it used to be, particularly in terms of the depth of analysis. It's more general these days. You can buy their professional services in order to get better support.

Most companies find it very easy to implement Tableau and to make an impact with their data because it's very easy to install, to learn and to start using. For larger companies we combine Tableau with other solutions, such as Vertica or Alteryx or Hadoop or Python. That's a big project but most companies first need to solve their self-service BI. They need to find insights into their business and with Tableau it's very easy to do that. In minutes, you can gain many insights and discover knowledge without being an expert of business intelligence, let's say. Deployment takes an average of two months, it depends on the size of the company.

We are always evaluating this solution in relation to Microsoft Power BI and QlikView. Power BI requires knowledge of numerous other Microsoft products in order to get results from your implementation. You need an expert DBA that can handle it in cloud and many specialists to implement the Microsoft solution. People think that buying or using Power BI is all that they need to do, but that's not the case, Power BI is just the last step of the implementation. A lot needs to be done before implementation. It's the same when it comes to automatizing the data refresh. Tableau has just three products and you don't need much time to learn and to finish a project and be up and running. QlikView has less tools and less features for data preparation. Vertica is another database that handles built-in models for data science and for the data scientist, this is a good choice in order to run, test and train the models.

It's important to understand your needs because if you only need to build dashboards, Tableau is not essential. But if you need a deeper business intelligence project, and you have higher expectations, Tableau would be the solution. If you only need to build some dashboards, you can use Power BI, it's a very good tool and it's cheaper. If your project is more ambitious then go for Tableau. Tableau has a lot of experience and can solve all the typical problems. I rate this solution a nine out of 10.

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.

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. 

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. 

I have been using this solution for five years. 

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. 

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

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. 

We use it for consulting and teaching purposes. We teach data science, and we use a data science tool. Most of the time, we use open-source tools, but we have also started to use some proprietary tools, such as Tableau. We will also explore other data science tools such as SPSS from IBM and SAS. 

We are using Tableau to teach students. We create a story on the data and teach them what kind of visualizations are more appealing to clients. The focus is on storytelling and what kind of visualizations are relevant for a specific business situation. 

We are using the latest version of Tableau, and it is deployed on my desktop.

From the data science point of view, we use it for model building purposes. For example, if we are using it for a bank and we want to understand how much loan the bank can provide, we can use visualization to show the educational qualification, salary, gender, and city of a customer, and by using this information, we can arrive at the loan amount that this person is eligible for. I can also use it to view all prospective customers, so essentially, this is going to help me in model building as well as in understanding and segmenting customers and doing forecasting and predictive analytics. 

We use model widgets, and we can create thousands of visualizations, such as motion charts and bubble charts. We can also create animated versions of the graphs and view the data from multiple dimensions. These are the features that we typically use and like.

I have used Power BI as well as Tableau. There are a couple of interesting features that I like in Power BI, but they are not present in Tableau. For example, in Power BI, if I am looking at country-wise population, I can type and ask for the country that has the maximum population, and it will automatically give an answer and address that query. This kind of feature is not there in Tableau.

Similarly, in Power BI, for integrating with the latest ML algorithms, we have decision trees and primarily multiple machine learning algorithms. The decision tree essentially visualizes the patterns in the data. We don't have such a feature in Tableau. If Tableau can integrate with the machine learning algorithms and help us to do visualizations, it would be a wonderful combination. Most of the people are going for Tableau primarily for visualization purposes. However, in the data science industry, users want to do model building as well as tell a story. As of now, Tableau is fulfilling the requirements for visualization purposes. If they can bring it up to a level where I can use it for machine learning purposes as well as for visualization, it would be very helpful. Many people who want to do data science don't want to write a code. Tableau is anyway a drag and drop tool, and if they can provide those options as well, it will be a powerful combination.

I have been using this solution for four to five years.

If I'm going to upload data of more than 10,000 records, then it might be unstable. With 10,000 rows and more than 100 columns, it really becomes shaky. However, this could also be because of the local infrastructure. For example, if I am using Tableau on my local machine with 4GB RAM, it might not be suitable.

There has been no need for scaling. We are actually connecting to an Oracle Database or SQL Server database, and we can take whatever data we require. We have 40 people who are using this solution in our organization.

We never took help from their technical support. We have experience in data science, and we know what kind of configurations are typically helpful. 

Its initial setup is very simple. We get the Tableau license code, and with a couple of clicks, we can set it up. It doesn't take more than two minutes to install it on our machine.

We implemented it ourselves. It doesn't require any maintenance for the purposes for which we use it. We use it for consulting and teaching purposes.

Its price is reasonable. Everything is included in the license.

Tableau is a wonderful tool, but you should know the proper methodology of using it and the specific situations for which it is helpful. This is very important. For example, we can use a knife to cut vegetables, but it can also cut my hand.

One should be able to understand the visualization that you are constructing in less than 30 seconds. Otherwise, the visualization doesn't meet the purpose. This is the benchmark that I have set myself.

I would rate Tableau a nine out of ten.

The dashboards give us metrics around the sales of our company. Most are sales reports to let us know how we're doing across different account managers, as well as how we're doing according to our forecast and plan.

The most valuable part of the solution is the general dashboard features. We schedule the dashboards to be refreshed and re-calculated, so they're not live connections but cached dashboards.

With Tableau, when you're dealing with very large datasets, it can be slow so the performance is an area that can be improved.

The security can be improved.

We have been using Tableau across the enterprise for approximately seven years.

We don't have any complaints about stability.

Scalability-wise, Tableau has met all of our needs. Across the organization as a whole, we probably have more than 1,000 users. There are probably 50 power users, who create their own dashboards and reports.

The consumers are sales executives, senior management, C-level, and HR. There are a lot of job categories that use the reports.

The technical support has been pretty good and we haven't had any major complaints about it.

We are currently using MicroStrategy along with Tableau. We began with MicroStrategy, and all of our reports were on it. We had been using it for about 15 years. Tableau is much easier to develop in, so with MicroStrategy, you needed more of an architect to manage the metadata. Because Tableau is a lot simpler to implement, we've been able to train people to do their own reports, so it's much better from a self-service perspective.

Security-wise, Tableau is not as robust as MicroStrategy.

The initial setup was pretty straightforward.

We initially had a third-party vendor come in and help us with the setup. They led that effort, but since then, we've managed the environments ourselves.

We have an in-house team that takes care of maintenance.

Tableau is not as cost-effective as Microsoft BI.

We are thinking about switching to Microsoft Power BI from MicroStrategy and Tableau. Cost is a factor that is driving us toward the Microsoft solution.

I would rate this solution a nine out of ten.

We use this solution to process and create reports for management. 

Within our organization, 10 people in marketing use this solution.

With Tableau, we can create our own reports which in turn, saves us tons of time as we don't have to wait for IT to do it.

Tableau is easy to use and it has great predictive features. 

It would be nice if we could export more raw data. Currently, there is a limit as to how much data you can export.

I have been using Tableau for roughly three years.

Tableau is very stable.

The technical support is pretty good.

The initial setup is quite straightforward. It's not too complex.

We deployed this solution on our own.

The price of this solution could definitely be lower. It's quite expensive. We're on a monthly subscription — I am not sure exactly how much we pay.

Tableau allows us to go deep inside the data — other solutions, like Excel, don't allow you to do that.

As a BI tool, I would give Tableau a rating of eight out of ten — it's one of the easiest BI tools available; however, it's not that easy to manage orders. It's really user-friendly for individual users, but it may not be suitable for large organizations.

Tableau is very good in the front-end visualization compared to Power BI.

The look and feel of Tableau are the best when compared with Power BI.

Power BI meets with my expectations but the wow factor is in Tableau.

An issue that is common to both Tableau and Power BI is with large data sets. When it comes to large datasets, the data should be extracted faster.

Tableau should offer the end-user a desktop version that is free where they can go in and practice. There are other solutions that offer it for free such as Huawei, and the desktop version of Power BI is also free.

People tend to know if they want to learn visualization. They don't have a proper tool in place, they don't know how to or where to go to learn. If you give them the tool to learn and let them explore when they want to go into production, people are able to purchase the license. A 14-day trial version would not be enough time.

If they want to be competitive in the market, the price must be improved.

They should allow more than a 14-day trial version. It should be a longer duration otherwise no one will want to learn it.

Tableau is $35, whereas Power BI is only $9.90. Tableau is not competitive and should reduce its price.

SQL is the most important. Writing SQL queries is very important and that's the first foundation I would recommend for any juniors to start.

If they're not very strong in SQL then they will not be able to write the functions for both Power BI and Tableau. SQL is the foundation for anything.

I would rate Tableau a seven out of ten.

I am into a new healthcare domain. I publish my dashboards and my audience are the providers.

I am not well-versed with the latest 2020 version of the solution, but I have heard that it has made parameters dynamic. For example, when we are publishing the dashboards, if we want the dashboards to be set as a default as the previous month, we do not have to modify it again and again. It can republish month after month using an assigned default. This will save me time from not having to redo the dashboard all the time. The dynamic parameters are amazing in Tableau, it has been improved in the latest version.

I love the customization skills that Tableau has, it is not restricted to what is built-in already. We have many customizable options and they come out to be very fancy and beautiful charts. Also, I like the extract feature that makes my dashboard run faster. The low-level security that Tableau handles works well. This solution is user-friendly and suitable for any type of user. Lastly, the dashboard and reports are very user-friendly to navigate.

This solution has some features which really needs to be improved. For example, the sorting feature, If we compare it with ClixSense, ClixSense has a direct sorting feature available to users. Wherein Tableau, we have to go and create a parameter, make it dynamic, force users to click somewhere else on the filter, and then maybe you can sort it. Tableau is really new for sorting features.

With performance tuning, it generates a pretty complex query when it is not required. We do not actually write 100 lines of code for a single KPI indicator. What we do is run the performance tuning model which will give 100-200 lines of code for a single KPI. That is not exactly an optimized query. While running performance tuning on the query, it should be pretty optimized, but it does not seem to be doing this.

I have been using the solution for three years.

The solution is fairly stable. However, the issue is when it is time to upgrade. Upgrading a Tableau server is too tedious compared to other tools where normally you just have an update EXE file you run and it is done. This is not the case with Tableau, it requires the dashboard to go down for an hour and then we have to republish all the dashboards again. 

The solution is scalable without a doubt.

This solution has the best technical support compared to any tool. 

The solution is expensive but it depends on the customer's needs which will determine the cost of the licensing. How much they require and what package they want.

We have evaluated ClixSense in the past. With ClixSense, it is not as customizable as this solution, I would even say restricted. For each and every customization and format change, the basic stuff, it asks us to buy another extension. We will not be doing that.

This solution has broadened my VA exposure and it has allowed me to do things differently with respect to VA concepts and visualization. I have a great takeaway from my experience with the solution.

I would recommend Tableau because of the amazing dashboards that are appealing and that also gives us the ability to create with far better customizations.

I rate Tableau an eight out of ten.