Tableau Reviews

I have found the solution easy to use and the interface is very good.

I have been using Tableau for two weeks.

The solution is stable compared to others solutions.

The setup was easy but we are having some problems with the configuration that is taking a long time. We have done some initial tests and some of the delays could be from bandwidth issues. However, the whole installation process should be simplified.

We have evaluated Domo, Microsoft BI, and Qlik, and we have found Tableau is much better.

I would recommend this solution to others.

I rate Tableau a seven out of ten.

I am using it for personal and organizational purposes. Most recently, we used it to collect and analyze the personal and geographic data input by people over the web.

Makes analysis fast and easy, providing insights that could be missed otherwise.

It is easy to use with very powerful data visualizations.

I am not a frequent user of this solution, so I am not sure what they've been doing recently. The last time when I used it, I had to use other tools with it for data extraction and cleansing.

Its price should also be improved. It is more expensive than Power BI. In terms of training, there is generally better online training for Power BI, but I am not sure of that. It would be helpful to know from where to access its training.

I have been using this solution off and on for four years.

It is stable.

It is scalable if you use it with other tools. I have used it with other tools.

I am a freelance consultant. I use it myself. My clients have hundreds or thousands of users.

I don't have any experience with their support.

I also use Power BI. Tableau is very comparable to Power BI.

If I remember it correctly, it was easy.

I can do it on my own.

My clients don't measure an ROI, they are interested in getting insights faster and when the get past the basics right then modelling scenarios. If you invest in BI tools it is part of a journey requiring investment. Analysis often helps to increase revenues and reduce costs. 

It is expensive when you compare it with Power BI. It should be cheaper.

I have looking at SAP SAC and Oracle / Essbase for a client.

I would recommend this solution. I would rate Tableau a nine out of ten.

We just created the data visualization and analytics models and the complete setup file was sent to the client for deployment in their own premise as that was their client policy. We just created the solution and the solution was transferred to them.

We were trying to create a dashboard for the contractors in an oil and gas plant. It's for a million-dollar company. That was the level one priority. The use case involved a pilot project meant to drill down the visualization of each contractor and the sub-KPIs at a sub contracting level, plus the geographies involved. Tableau is a data visualization tool with analytics involved in it. The art was to create a set of dashboards that were geography-specific plus contractor-specific. Along with that, there were some common KPIs against which the visualization was supposed to cover as well.

The best part about Tableau is the visualization. 

Tableau has some amazing features. We can have some additional UI features that act like a skin. You can get it to really customize to your needs and then you can incorporate items as a plugin in your Tableau version and the user interface.

The graphics are quite good.

The solution can scale.

Technical support was helpful.

We found the solution to be quite stable.

Tableau is good, however, it lacks a bit on the integration side if you compare it to Power BI, for example. Power BI has quite a good amount of connectors. Even though Tableau does have some, Power BI works well with the Microsoft environment and most of the firms are in granular detail. That's where Microsoft shines. Maybe Tableau can collaborate with other bigger, well-recognized solutions in order to get an edge in the market the way Power BI does with Microsoft. 

The pricing is a bit expensive.

There's a bit of a learning curve for those new to implementing the solution.

We've been using the solution for less than a year so far. In the last eight months, we've developed and deployed the solution. We haven't been using it as long as, for example, Power BI.

It's a reliable solution. There's no doubt about it. The solution is stable. It does not crash or freeze. There are no bugs or glitches.

For deployment, the capacity was increased. It required really strong contractors also. That was easily manageable. It is quite scalable.

We had a team of around 20 developers who are working on the solution.

We only dealt with technical support once or twice. There wasn't a lot of interaction in the time we used Tableau. That said, they were always helpful and responsive. We were happy with their amount of assistance. 

We are also using Power BI. We use both products currently.

For us the solution's initial setup was complex as we were just aware of how to use Power BI previously. It was a completely new solution. We had to get an instructor to get the things in place.

I'd say it was about an eight-month installation process for the particular software. In-app work was one month and then seven months of development everything and all over the board.

We had an instructor assist us in the implementation process. and show us how to use the product.

We bought a monthly license as we were not able to continue with it long-term. It was simply a specific client requirement that was not needed forever.

The pricing of Tableau is a bit on a higher side compared to Power BI, however, for us, it didn't matter much as we were charging it to the client. That said, for a normal end-user, it would be considered a bit pricey compared to Power BI.

For Tableau we have been using only for a specific team within that also was for the external clients. That experience was only around eight months. However, it was a pretty good experience. Up to that point, we had been strictly using Power BI. Adding Tableau was for a specific client who just wanted the Tableau licenses created and developed for them.

We were using the latest version. It was not a cloud version. It was the desktop on-prem version we were using.

The solution would work well for small, medium, or large enterprises. It caters to all different sizes of companies.

I'd rate the solution at an eight out of ten overall. We've mostly been quite happy with it.

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. 

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.

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.

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. 

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.

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. 

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.

We also use Power BI.

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. 

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

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

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.

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.

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.

I have been using Tableau for three years.

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.

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.

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.

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. 

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.

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.

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.

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.