Tableau Reviews

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.

We have used it for our program correspondence, basically, so how to program report to satisfaction of different programs. It helps us obtain information. We also use it for visualization.

It allows us to basically understand and evaluate our numbers in an expedient manner. It doesn't require us to need a huge number of data bases that we need to manage. This solution sets everything up for us. It has a good ease-of-use.

In the past, we were using several different solutions, and the packages were insufficient for our needs. We used a lot of different software solutions, and extreme Excel, but it wasn't enough for our needs. We were also looking for something that was a bit more user-friendly. 

One of the most valuable features are the different visualizations. It makes it much easier for us to represent what the data is showing. The dashboard is great, and the visualizations are really what we focus on. 

It's as powerful if you know how to use it, so it's made as much as we know how to use it. It's enough, but there's much more of a need to understand what you do to operate the solution. To be able to do more, we need to set it up to do different things. It is fine, but we have not really invested time or people into doing this much.

I would like to be able to set the parameters in a more specific manner. I feel as if it's not a questions of whether the solution is sufficient, it's whether we understand how to use it to the best of its productivity.

It is a stable solution. I think we can use it for a while for a lot of different things. Again, we do not know the full scope of the capabilities. I think we are using it the best we can, but we could find better ways for it to best suit our needs. So, we just need to learn how to use it more efficiently.

The technical support is good. They give solutions to our questions. 

We previously used Microsoft BI.

I was not involved in the initial setup of the solution.

Most people buy software because they know that it will help them do one thing, but they use it a tenth of the potential of what it could be used for. So, if you don't know what that is, you're stuck at ten percent. Be sure to explore the full capabilities of the solution.

The price is competitive. We always consider pricing when considering a new solution. We are a non-profit, and pricing is a huge concern.

We always like to evaluate other products in tandem with what we are using.

When reviewing a possible solution, we always consider:

• Price
• Functionality

Operations Perspective:

The most valuable aspect of this product is the ease of deployment from the Tableau Desktop to the server, providing the ability to either connect live to a data source or create a cached dataset that can be published and updated separately. The deployment of a Tableau Workbook can even be packaged up and sent to someone with a Tableau Reader installed. This makes the solution very agile and scalable.

The ability to deploy is the added ability to centralise the Tableau repository for all Tableau Developers. We have initiated a central shared directory for each Tableau platform, Dev, UAT, and PROD with each containing subdirectories for each Tableau Site and Project. Being a financial institution we must provide data segregation to comply with legislation and Data Governance policies enforced by brand segregation.

Development Perspective:

Ease of use is the most common call out from the developers. There is a thriving user group online that provides any number of ways to build reports quickly and easily, but the most important ability is to allow the Developer to storyboard the information in a dashboard. Tableau provides the developer a means to provide captions and business information on the dashboard to tell the story of each Workbook. This ability to break down a complex Workbook into an easy to digest narrative provides the business stakeholder a way to really understand and discover the story behind the data giving them the necessary insights and metrics.

Tableau has provided the organisation a means to allow business people to explore their data at their pace. They can either review the reports online, or on their Tableau Reader or they can download it into other formats for use in data analysis. The key insights and graphic representations through the dashboards has also provided them a quick and painless overview of their current status, whatever that may be.

At this stage, we haven’t had any suggestions since moving to Tableau 10.3, so there may be improvements requested further down the line.

Six years.

We did have issues with Tableau 10.1 server with the brokers failing on heavy load but since moving to 10.2, then to 10.3, this issue seems to have been resolved and the environment is now quite stable.

This is no longer an issue in Tableau 10.3.

A nine out of 10. With all first line support, sometimes these support people need to read the question a couple of times before responding, but this is typical of any first line support for any vendor.

We are still using another solution. However, this will be shutdown next year due to the decline in development on this platform. The development cycle on this legacy platform has been too slow for any type of turnkey solution and the end result did not provide a proficient self-service capability that satisfied the customer. Performance has been another factor in this platforms decline.

The initial setup of Tableau had been developed with a DevOps lens. I wanted to build a platform that had rigor and a platform with a level of governance of aspects which could guarantee report certification and certainty for the business stakeholder. These processes were carefully thought out even before the product was installed.

Once the process was developed and tested, we rolled out the solution to the business with a migration form for developers to fill out as we needed to meet audit policy guidelines and brand segment legal requirements. We allocated several business people to be software advocates whom were familiar with the migration requirements and liaised with the business to guide them in their approach to using the Tableau solution.

After six years, we can confidently say that any report in production is guaranteed to be correct (within limits) and the data source has been certified for provisioning.

At the time, this did have pushback from the vendor, but we’ve seen the chaos caused in other organisations that we mitigated right at the start.

Buy 50 at a time. Project your use base every three months, and project your requirements forward, so you can meet demand for licenses by having them available.

We have also added the vendor into our internal order system for ad hoc requests that we meet the needs of those that want a license on their own terms.

Actually no. This was a spontaneous purchase by an executive and we basically ran with it.

I’d strongly advise going to the forums, attending the Tableau conferences, and ask questions about governance, report certification, and capacity. These questions and the corresponding answers should guide you on how you would best implement your own solution. We did not want to be dictated to by Tableau to install it as a free for all. We wanted to future proof the product and provide certainty around the reports being developed and deployed to the business.

I have been using Tableau to visualize data sets. The three features that are most valuable to me are:

• Ease of use. Most of the configurations are accessed by drag and drop, so very little actual programming is required.
• Interactivity, especially the ability to use tool tips to identify exactly which points are plotting in an unusual or unexpected position. This is the first step in distinguishing outliers from important data features, which is an important part of data exploration.
• The ability to easily annotate and export finished plots for presentation purposes.

I have previously used Excel or R to perform exploratory data analysis. Tableau is easier and quicker, which means results can be obtained more quickly.

Some of the command choices have to be memorized and are not intuitive. It could be even easier to learn.

I have used it for about three months.

No issues with deployment, except I wish a version was available for Linux (Ubuntu).

I haven't needed technical support yet.

I previously used R for data exploratory analysis. I'm choosing Tableau because it is quicker, and exploratory data analysis by its nature requires a large variety and volume of output.

Initial setup was very simple; standard Windows installation.

Just me... No problems. Just note that Tableau workbooks are stored in their own file structure by default, not in the file where the data originated or where the exported charts are stored.

Tableau has a free trial, free versions for academic scholars/faculty, and a free public version. The paid versions are a little pricey, but likely worth it.

There is a public version you can implement for free. Its main restriction is the variety of data source connections that it supports. You can still work with the typical text or Excel files, but live database connections are not supported.

I think it's great at what it tries to do.

I use it for management control and for balance sheet analysis. As corporale finance consultant, the core of my job is financial analysis/modeling. I added Tableau to my workflow to improve the decision making process of my clients make decisions but I found it very useful also to produce reporting for Financial Istitutions, Investment Fund, etc.

Tableau has improved the way our clients “read” what’s happening in their company, 

I think one of the best feature is usability: understanding  dragging & dropping Measures & Dimension is so simple that you can easily learn the software.

Tableau is very intuitive, it has not a deep learning curve so you can build your dashboards in short time.

The forecast instrument. I still use my primary software (that is Quantrix Modeler) to build my financial models. 

I’m not saying that is a “static” platform at the moment, it’s dynamic due to the fact that you can build parameters, however it's not the same as a spreadsheet in which you can write formulas and algotythms that are more and more complex. 

I have used Tableau since 2018. It's been about three years.

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

The solution can scale well. There shouldn't be any issues if a company needs to expand. 

I've dealt with technical support in the past. Two years ago I had a problem, a technical problem. It was a very serious issue with the software in my first installation and I came in contact with the engineer in London. They solved my problem very, very quickly. I've been quite satisfied with them overall.

The initial setup is very simple. It's not overly complex or difficult. A company shouldn't have any issues. 

While I handled the implementation myself, I chose to do a period of learning with the Information Lab a Tableau Partner company.  I took two courses to have a better understanding and to more quickly understand the possibilities I had to work with.

I have a Tableau license. It's very, very cheap. For the use and the capability of the software, it's $70 per month, it’ an awesome price.

Yes I did: MicroStrategy because , it was the first competitor of Tableau. However, there is no comparison. Tableau's the best platform for me and offers the best software.

We are only customers at this time. 

We are focused on producing and using Tableau only for our clients. We bought a number of view licenses and we give them to our client so they can use Tableau via the online version.

I'd rate the solution at a ten out of ten. I've been very pleased with its capabilities. 

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.