Tableau Reviews

I have used Tableau in the past with other clients for enterprise-level data visualization for financial and manufacturing industries. I have also used it for documents dashboard and different kinds of KPI visualizations. I'm currently using it for academic purposes. In my current organization, we are not using Tableau. We are using Power BI.

Tableau is very flexible and easy to learn. It has drag-and-drop function analytics, and its design is very good. It is a very good tool, and it basically brings life into data with good design. We have been creating a lot of interactive visualizations and dashboards.

It has a public version. There are public communities from where you can get a lot of examples for practice.

Its price should be improved. Its price is much higher than Power BI and QlikView.

Programming is not easy on Tableau. For programming, you have to have a separate model. They should include programming directly on the web portion of the Tableau desktop so that people can write Python or JavaScript code for customizations instead of using a different model. Currently, Tableau Data Prep is a separate application that you have to purchase. It would be helpful if they can include Tableau Data Prep and programming languages such as R, Python in the next version.

Tableau Public, which is a community version, doesn't allow you to save your work on your desktop. They should allow it. Currently, you can only upload it in the community.

I've been using Tableau for almost eight or nine years.

It is very stable. 

It is scalable. They have a cloud version, and you can implement it on the cloud.

Their technical support is good. Our own IT can also manage it, and I can also get support from Tableau.

We also use Dimension, Power BI, and QlikView. Domo is also there, but Domo is a little bit more expensive. Microstrategy is also a little bit more expensive, and it has different media storage.

Its installation is straightforward. It is a one-click installation. 

I installed it myself on my laptop.

Its price is higher than Power BI and QlikView. Tableau costs around $70 per user per month, whereas Power BI is around $8 to $9. QlikView is around $30. 

Tableau has various prices for various models such as Creator, Designer. 

I would recommend this solution if you do not have budget constraints. It is a very good solution with excellent visualizations. I plan to keep using it for academic purposes.

I would rate Tableau a nine out of ten.

Our primary use case of Tableau is to elaborate and demonstrate output from our big data solution. For example, we use it for finding out the best location for cases, such as fraud cases. Presently, we are using Tableau to find out the original fraud case, the initiator of the fraud process, and the network. Tableau is used with our big data solution, so it's embedded there, before Oracle even. 

Tableau is deployed on-premise. In my organization, we have a very strict environment, so we don't have a policy for having anything on cloud. 

A valuable feature of Tableau is that it is a useful tool for small setups. I shuffle between Tableau and MicroStrategy, so I use Tableau for personal purposes more than enterprise. I like the light version of Tableau for personal usage and doing some use cases on my own. When it comes to something small, I use Tableau for setups, rather than any other tool. 

I think Tableau could be improved with cheaper or more flexible licensing, though this is a generic improvement and applies for any product. It would be better if they had more flexible payment and licensing plans so that they could suit small- and mid-sized organizations. 

I have been using Tableau since 2016. 

I haven't had any issues with stability. 

Theoretically, Tableau is scalable, but I haven't tried to scale it yet. 

I have never contacted technical support. 

I shuffle between available tools—I also use MicroStrategy, Microsoft Power BI, and Qlik. 

Before using Tableau, I used Oracle BI, Oracle ODI, and Teradata. 

The installation was an easy process, and I've done it myself twice. I'm a technical guy, so I didn't need a technical team to help with deployment, I did it on my own. 

I implemented this solution myself. 

We pay for the enterprise license for Tableau. The licensing could be cheaper and more flexible. 

I rate Tableau an eight out of ten. I recommend Tableau, and I even recommend it here in my organization. Their plan was to replace it with Qlik, but I did an assessment and advised them not to pay extra costs for other tools when Tableau was already in place in our organization. 

Right now I use Tableau for learning purposes, such as open data sources, trying to learn the various visualizations that can be done on it.

I liked the representation of the geospatial map. It was really cool to have that visual and be able to create hierarchies using the geolocation cities, states, just wording those names into appropriate provisions on the map. So that's really something nice. I feel the visualizations come out very pretty.

The price is definitely a point that can be improved because smaller firms, like my bank firm, don't use Tableau because it's an expensive tool. If there were an option that catered toward smaller firms, that would be great because Tableau does in fact help with a lot of different kinds of data sources. For instance, it lets you upload CSV on Excel. However, other tools that we currently use, such as Looker, do not let you upload Excel files for ad hoc analysis. So, definitely, this is something price-wise that can be catered toward smaller firms.

Creating variables, creating new fields in Tableau during analysis, actually adds columns to the data. That's something that could potentially give us an option. Do you want it as a column added to the data set or do you want it ad hoc in the visualization sheet? So if you create a measurement or a dimension, that creates a new column, but if you try to create a new filter directly on the visualization, it doesn't let you rename it. Basically what you see is just the calculation that you put in there. If you wanted to create something without making it an extra column in the data set, you can't just rename it to a more user-friendly short name. An improvement would be adding the ability to rename ad hoc creations if you do create a mark or a filter on the visualization. That doesn't really get added to the actual data fields.

I've been using Tableau for a few months now as a learning, research activity rather than a day-to-day activity at work. So I primarily was going to a Tableau Public Learning.

As of now, I haven't had any issues with the stability of the solution. Not any glitches.

Given that it's Tableau Public, I don't feel I could give the right answer to that. However, given that you could share your visualizations on a server without sending a file to people, scalability seems like a good option here.

I have not used their tech support, but I did refer to a textbook to learn how to use Tableau.

Tableau has resources for learning using videos as well.

My company currently uses Looker, not Tableau. I've been working on Tableau on my own time outside of work, trying to learn their free application, Tableau Public.

The setup was pretty straightforward. It doesn't take much to get it all set up.

Tableau is an expensive tool for smaller firms.

Do take time to learn the solution, because Tableau has a lot of features, a lot of complex visualization features that can make the visualization pretty powerful. I would advise people to learn it completely so they can use Tableau to its full extent rather than just ad hoc simple visualizations.

I would rate Tableau right at 8.5, leaning toward 9.

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 the solution for the client's management of KPIs; it involves monitoring various aspects. If they are a manufacturing company, key performance indicators revolve around production and other relevant factors.

The solution helps users create dashboards and analyze data without relying on IT or product teams. 

The tool's OpenAI integration was announced last year. However, it is late. Tableau is a good solution for end customers. However, there are some concerns regarding the stability and performance of its server architecture, including SaaS services. The server side appears unstable, and performance issues are noticeable, often accompanied by unclear error messages.

I have been working with the product for seven years. 

I rate Tableau's stability a nine out of ten. 

Our experience spans around 70 customers, covering manufacturing, pharmacy, trading, construction, universities, and the public sector. I rate the product's scalability a seven out of ten. 

The tech support takes too much time to respond.

Neutral

I rate the tool's setup a ten out of ten. While setting Tableau servers for customers, we often encounter challenges that vary based on their network configuration and operating systems, such as Windows or Linux.

In Korea, the tool's pricing depends on the scale of usage. For instance, it's reasonable for a department with fewer than 50 users to adopt Tableau, like sales. However, the pricing becomes an issue when considering an enterprise solution for a larger user base, say 10,000 people.

Tableau is integrating OpenAI's GPT feature. It will help to create automatic dashboards with natural language. Only ten percent of our customers use Tableau in the cloud since they prioritize their data. They don't want to import their data to the cloud. It is as per their policies and security advice. Traditional companies don't like exporting customer data outside the organizational network. 

Japanese data centers often support Korea. However, the challenge arises from the absence of a federal cloud data center in Korea. Consequently, utilizing Tableau Cloud may result in data being exported outside the country. This is not allowed legally for financial entities such as banks. 

However, the government does not regulate smaller companies like startups. Hence, they are more open to the cloud. This is not the case for public entities. They should install the software in the government's cloud. 

Our clients for Tableau are mainly enterprise businesses. I rate it a nine out of ten. 

I primarily use Tableau for fair-market reporting.

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

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

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

I customize the reports to my needs and preferences.

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

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

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

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

I have been using Tableau for close to five years.

In all aspects, Tableau has been very stable.

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

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

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

They have a good knowledge forum.

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

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

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

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

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

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

Tableau is a solution that is near-perfect.

I would rate this solution a nine out of ten.

We are using Tableau to make a dashboard used by our internal users, and then it is being used for a KPI report. This part is also shared with our customers. The customers access the web, and they check some limited version of the KPI report.

We are using the Tableau server for clients and desktop. The solution is deployed on-prem. We are kind of a 3PL provider, and we are using Tableau to meet the requirements of our customers. We are implementers.

We introduced Tableau because it provides many features that can be customized by users. We provide training to make the dashboard look how our business side wants, and they are manipulating the dashboard for their needs.

On the technical side, we are IT support and sometimes we provide some education and information on how to use the solution.

I think it would be much better if Tableau provided some API-based integration. I did try to integrate the Tableau web page and web dashboard into our own application. Some parts were successful, but other parts have some open points. If Tableau provided this kind of package with some integration, it would be much, much better.

The most valuable feature is that we can integrate with our own database, and it will display the KPIs. This is highly required from the business side.

An improvement would be changing the design of the layout of the dashboard from the business side. Sometimes there are requests for the possibility to enhance the performance and the data depending on what they need more of. It depends on the situation.

I have been using Tableau for about four years.

It's already using 32 gigabytes of memory, but the performance is not so good. It's very heavy.

We have roughly 20 people using this solution. Most users have the role of logistics operator. Most users are doing their job regarding logistics, and they take more effort to make dashboards.

Currently, we have a strategy to open the reports to all customers, but I think we should develop more business-related skills, not only with the system or in some application terms. Our users do not have enough skills or insights for the dashboard.

We are doing our own technical support by searching the technical Wiki or things like that.

Initial setup is straightforward because it's a simple concept.

I'm not sure how long deployment takes because this is usually managed by our data engineer. There's no strategy regarding deployment itself. We just make some temporal or test dashboard and then communicate with our users. After confirming, we just announce it with email, and then they start to use it as an official version of the dashboard.

We didn't use an integrator, reseller, or consultant for the deployment. The number of staff required for deployment and maintenance just depends on the case. Sometimes it will be simple, so there are only two or three people to make suggestions. After they apply that, sometimes we officially open it.

Basically, we prefer a permanent license. A one-time charge is much better.

We didn't really evaluate other options. Every application provides some concept of a dashboard in using the data in that application. We have our own homemade dashboard and our business application, but users normally don't use it.

I think Tableau has many features for display, like graphs or pie charts. We can change dynamically, but our own dashboard doesn't provide that. It takes much more time if we change the layout there.

I would rate this solution 8 out of 10. Tableau has many features, and it's very nice, but it is very heavy. Tableau has to consume a lot of server resources.

It has many options and features but it's complicated. The users are having problems or difficulties to adapt or to learn the Tableau software because there are so many features. The many possibilities means that users should run a lot of it. It takes time to get used to Tableau. From my point of view, it's harder to learn.

For those who want to implement this product, I recommend that they research it themselves.

Tableau is pretty intuitive. It has a great interface, and you can get multiple visualizations. The best thing I like about Tableau is that you don't have to go for creating; it is calculated free. Unlike Power BI, Tableau has create a calculated column with dimension.

Tableau is quite fast and provides connectivity to 75 plus data connections, which is great.

Also, installation and configuration are pretty fast and seamless in Tableau.

In Tableau, it's just the concept of creating one calculated column and one create calculated free. So, it's pretty simple, and it's pretty easy to locate and work on it.

I have noticed that Tableau is not very compatible with ClickHouse. There's no direct connection to ClickHouse; you have to set up an ODBC connection.

Tableau's performance takes a hit if you have huge data. The stability and scalability could be improved.

I've been working for almost five plus years on Tableau.

Tableau's performance takes a hit if you have huge data. So in terms of stability, I feel that Cognos would be more stable because you can import all the metadata and store it in the Framework Manager. Tableau has scope for improvement regarding stability.

Tableau needs to be more scalable. The performance takes a hit if you have huge data. Even if you take an extract and you publish the extract and schedule it to refresh, if the report has multiple tabs, it can take quite a while to go from one tab to another.

We are going to scale the Tableau server so that it can accommodate more processes and can be more process inclusive.

We have a Center of Excellence team, and anytime we have an issue, we reach out to them. They then raise an incident or a ticket with Tableau technical support. In the case where we had 1 million rows and the Tableau data was failing to refresh, we shared the log with Tableau Center of Excellence. They came up with the findings that it's more of a database issue and not a Tableau server issue.

Installation and configuration are pretty fast and seamless in Tableau.

In general, if someone is new and wants to learn Tableau, it's around $70 per month.

I have experience working with Cognos and Power BI. Compared to Cognos, Tableau and Power BI are pretty fast. Cognos has the concept of Framework Manager where you can build a framework model. Once you build the model, then you have to release the package, and only then is the subset or the package of data available for reporting. Tableau and Power BI eradicate the dependency on a framework model.

With Cognos, installation and configuration wise the setup takes a bit of time. You have to install and configure and then make the data available. After that, you can do reporting. Unlike that, Tableau is very quick; you can just directly connect to Excel or a file on your desktop.

The connectivity, installation, and configuration are pretty fast and seamless in Tableau and Power BI, unlike those in Cognos.

From a license perspective, I think Cognos is the most expensive, then Tableau, and then Power BI.

If I were to rate these solutions on a scale from one to ten, I would rate Power BI at 7 and Cognos at 8.

You can do a lot in Tableau, and on a scale from one to ten, I would rate it at eight.