Tableau Reviews

We use the most recent version. 

We use the solution to engage the field teams and we integrate that with the data warehouse data and build the dashboards for them.

It is helpful that the solution provides access to one's own data. It allows a person to get insights out of the data provided by his tool, based upon the KPIs that the person wishes to look at. It all depends upon different use cases. We have dashboards for marketing people, field teams and executives. It all depends upon which insights a person wants, in which case he can prep the data accordingly. This is good. 

The most valuable features are the visualizations, the way they show the combination charts. This allows a person to jointly put in different measures in different axes and greatly facilitates the user in understanding the data better.

There should be a focus on memory data, which is the concept of Tableau. This is where they squeeze the data into their memory. Because of that, we see performance issues on the dashboards. The architecture should be improved in such a way that the data can be better handled, like we see in the market tools, such as Domo, in which everything is cloud-based. We did a POC in which we compared Tableau with Domo and performance-wise the latter is much better.  

As such, the architecture should be improved to better handle the data.

We are seeing a shift from Tableau to Power BI, towards which most users are gravitating. This owes itself to the ease of use and their mindset of making use of Excel. Power BI offers greater ease of use. 

For the most part, when comparing all the BI tools, one sees that they work in the same format. But, if a single one must be chosen, one sees that his data can be integrated at a better place. Take real time data, for example. I know that they have the live connection, but, still, they can improve that data modeling space better.

We have been working with Tableau for almost seven years.

The solution has pretty good stability. It's a robust tool, even though it has a steep learning curve. But, still, I feel that from the stability perspective, it's a leading BI tool in the market. It's pretty stable.

I personally don't like any BI tool to have that scalability. What we usually do is integrate scalability into our warehouse layer. We know how to scale up and down and we handle it there. We don't rely much on the BI tools to do that.

I am talking about the scalability of a program in general, be it in its relation with users or as it concerns dashboards. 

We recently started working with Tableau online and that particular solution is scalable. It ingests the hardware, the server capacity by itself. So, if users go from, let's say... 100 to 500, we don't see a dip in performance. It still behaves the same. Because of this new integration technology with the cloud, they are scalable in that regard.

We are in contact with technical support. One service we have is Tableau online. If we see a dip in performance, we raise a ticket to the Tableau support team, work with them and make certain they address our issues. I would rate my experience with them as three out of five. 

We used Tableau from the get go. 

While I was not directly involved in the setup, I know that it's not that easy. There is a need for a proper administrator who has experience in that field.

We used an integrator from Tableau when implementing.

Our experience was good and we were assisted with our implementation requirements. They were able to make notes to match our use case and answer all of our questions, including those concerning the number of users we have and how to set up the server.

I'm not part of the administrative group which handles the setup. I am mostly a consumer and responsible for building the desktop. I use the desktop version to build the dashboards and am not responsible for the server health check or maintenance. As such, I am not in a position to provide information about the staff required for maintenance, updates and checkups. There are a couple of people who are responsible for this, one from the customer side and another from our team. Both parties are in sync when undertaking these activities. 

I have no knowledge concerning the licensing costs of Tableau. 

The solution is mostly deployed on-premises, although we have also done cloud-based deployment. 

We have around 500-plus users making use of the solution and mostly 90 percent are viewers. We have very few creators or explorers. Creators comprise seven percent and explorers three percent. 

My advice to others would vary depending on their use cases, what they're looking for and the level of competency they have within their organization to use it. Tableau has a steep learning curve. So, it depends upon one's use case, the reason the person is going with that specific BI tool. The procurement department would need to evaluate the use cases very carefully, because there are so many BI tools available in the market. One's focus should be more on a centralized tool when bringing a new one to his organization. It should address all the answers to one's users, like what they're looking for. Definitely Tableau is good in the data discovery part and it can handle large data sets. So, all of these things should matter when one is trying to evaluate a tool.

I rate Tableau as a seven out of ten. This is because we are using it and it has a steep learning curve. It's not user-friendly. One must build a competency in creating the visualization and then support it. All of these things matter when one is evaluating a tool. That's why a shift is going towards Power BI.

We primarily use the solution for data visualization and data analytics. I normally use it for analyzing data from social media, for social media analytics, mainly Twitter and data from the Twitter API. I use it to analyze what is being said on social media and also to look at the interaction on social media on specific topics. 

I also use it for educational purposes. I analyze the data from student information systems to check about their student progress and provide visualizations about this data.

I create a lot of dashboards, mainly using these tools. 

Tableau helped our organization to provide our ckients organizations with cloud-based  Data Analytics service. Through using the Tableau's anilities in the field of Data Analytics, and Data Preperation & Transformation, and Data Visualization
we collect, cleanse, transform client’s data and discover insights and patterns in this data. Using Tableau, we help our ckients to improve the way data is utilized to support the decision-making process, enhance strategy implementation, and apply KPI monitoring within the business process. Tableau helped us to provide our clients with data driven decision making power through utilizing high quality  data analytics and vizualization so that they can continue to comply with the standards and best practices in teir field of business.

The solution is very flexible. The ability of filtering and segmentation of the data makes it very flexible compared to other tools.

The ease of use is great. It's a good platform from an ease of use point of view. It's easy to use and easy to learn. The learning curve is not difficult to grasp. 

The user interface is very friendly. The onscreen help, and also the resources that Tableau provides, including training videos, a support website, and knowledge base, are very helpful. 

I use the Tableau training portal and I found it very enlightening. It provided me with online training and certifications. I use it mostly for strengthening my abilities in Tableau.  

I like the way it integrates with multiple data sources. The data blending aspect of Tableau, in which I can blend and merge data from multiple sources, is great. I found that the things that I was doing previously, such as using SQL or other tools over the course of hours I can do in Tableau within minutes. Instead of doing my job using SQL with multiple queries and instructions, now I can do it in Tableau in minutes.

Its ability to handle large amounts of data is very important. 

The initial setup is easy.

I would like to have the product be more flexible in terms of creating online shared dashboards. When I need to publish a public dashboard, I use Tableau Public. However, I don't find it flexible compared to Tableau Online, which is the paid version. Tableau Public is a free Tableau portal in which I can publish my data, however, Tableau Public doesn't provide the flexibility that I find in Tableau Online. If we compare this with other tools, such as Zoho Analytics, for example, publishing web-based shared dashboards is more flexible, in terms of publishing web-based shared dashboards.

If they can add the feature of machine learning and the predictive analysis to Tableau, it would be very helpful. After Salesforce acquired Tableau, they have been merging Salesforce with Tableau, in terms of machine learning. That said, in this case, I need to use two products - Salesforce and Tableau. I want to have the Einstein tool, which is available now in Salesforce, be integrated into Tableau, so I don't have to use Salesforce for machine learning, to use the Einstein tool, and I can use Tableau for the product. If the Einstein tool for machine learning is integrated into Tableau, that would be very good for us.

I've used the solution for around four years. 

The stability has been good. In general usage cases, it's reliable andhere are no bugs or glitches. It doesn't crash or freeze. But we face some stability (crash or freezsing) and performance (slowness) issue with large datasets especially when we export our Tableau visualization to Tableau Public.

Basically, I'm the one using it. However, others consume what I make. I create the dashboard, I create the analytics, and I give my analytics as a shared dashboard or as reports to the decision-makers and other employees. Normally they consume what I do, however, for the creation of dashboards, creation of analytics, I do the job. I'm the main user in that sense. 

It's very scalable, especially if you choose the online option.

Technical support has been great.

The implementation process is not difficult. It's very easy. When I use Tableau Online, it is given as software as a service, which means I don't need to deploy anything. I just give the username and password, and I use it directly without any issue. For the Tableau Desktop, I need to install the software. It's a very normal installation and happens without any issue.

We handled the implementation process ourselves. It's pretty easy. therefore, we didn't need outside assistance. 

The return on investment from Tableau is very high.

The pricing of the solution is very good. We find it much cheaper than other options.

I'm just a customer and an end-user. I have tried several times to have a partnership with Tableau, however, it seems a little bit difficult getting the partnership. This is maybe a negative aspect in terms of having a partnership program. It's not easy to have a partnership or a fellowship relationship with Tableau.

I'm using Tableau Online, as software as a service, and I'm also using Tableau Desktop. I use it on my machine.

I really recommend it for any organization that wants to have data visualization with a tight budget.

I would rate the solution at a nine out of ten.

We use it in our parent company as well as in client companies. A few of our environments are on-premises, and a few are on Tableau Online. We have a mix of both.

The UI part is the best. The end-users can easily get started with Tableau Desktop or Tableau Online because of its user-friendliness.

I also work as an SME on the platform side. Tableau is very nice and jazzy for the end-users, but there are pain points for the admins. Performance is something about which we hear a lot of complaints, such as the dashboard doesn't open in time. It performs well on the desktop but not on the server. I know that there is always a limitation when it comes to a huge amount of data or the complexity of the calculations, but we often hear from end-users about the performance on the server side. It is easy to drag and drop all the columns and do what we want, but if it is not going to load better on the server, users are not going to like it.

Their standard support is not good. They should improve it. I don't know if it has anything to do with the acquisition, but lately, their support has not been great.

Their upgrades have always been an issue. They never work. 

Tableau is a little bit costlier than other tools such as Power BI.

They should make it easy to integrate with tools like SharePoint, Teams, OneDrive, etc. Its integration with Office 365 should be improved because most of the users already have tools like Outlook, Teams, and SharePoint, and they want to integrate a reporting tool or a visualization tool with their existing tools. 

It is very easy to integrate scripting in Spotfire. We can do a lot of changes in the UI by writing some scripts. That could be something that Tableau can look into. They can also consider providing APIs, but most of the people who work with Tableau do not really work much on the scripting side. So, I am not sure if it is feasible or required technically.

I have been using this solution for almost eight years.

It is scalable for online and on-premises versions. With the online version, they take care of the load, and we don't have to worry about that. For on-premises, initially, we used to have core-based licensing in which we had a cap on the number of cores we could expand to. We then moved to user-based licensing, which makes it easy to scale.

In our parent company, we have close to 200 users. We also have two clients on this platform. One of the clients has about 400 users. For another client, overall, we support close to 20K customers on this platform. That's one of the biggest environments.

Their premium support is really good, but their standard support is failing. Their standard support is the worst. We recently had an experience where we waited for more than seven days for a ticket to be picked up. It was vacation time, and there were a lot of factors, but their standard support is not good. For a few of our clients, we do have premium support, and they respond to any issue because we include the technical account managers in the communication.

Comparing it with Power BI, the main differences are the cost and the integration with Office 365. It is very easy to integrate Power BI with Teams or SharePoint because they all belong to the same company, whereas with Tableau, I have to integrate it with a third-party vendor. It is a little tough to integrate Tableau with SharePoint or Teams. Nowadays, everyone wants everything in one place; it could either be in SharePoint or in Teams. 

I have been working with Spotfire lately, and it is very easy to integrate scripting in Spotfire.

The Tableau server-side used to be very good initially, but for the last year, we are having issues with the upgrades. Their upgrades never work. We always get stuck while doing the upgrades, and we end up taking a different approach. We take the data and keep it somewhere. After that, we wipe out the entire server and install it again. We then restore the data into that environment. 

In terms of maintaining this solution, I used to belong to level three (L3) support till last month. We were only handling the performance issues and any issues that need RCA. The L3 support used to have close to five people. L2 support, which usually included adding a user, removing a user, adding a new group, and providing usual production support, was taken care of by the Ops team. They used to have more than five people on the team.

Cost is where tools like MicroStrategy, Power BI, or Spotfire come into play. Cost-wise, Tableau is a little bit costlier than other tools such as Power BI.

I have been using Tableau all these years, but about four years ago, Power BI came out at a very low cost. Their desktop version was free from the beginning. Power BI Desktop has always been free, whereas Tableau Desktop is costly. When it comes to cost, people prefer Power BI because it integrates very well with Office 365. You don't have to worry about integration with Teams or SharePoint.

It is easy to use for most business users, but before using it, you should understand the basics of dimensions or measurements. If you directly come to this tool without understanding the concepts of warehousing, dimensions, and fact tables, you would not get what you want. This applies to any reporting tool. You should have a basic understanding of what data warehousing is all about and then get started with the tool.

I would rate it an eight out of 10. Tableau has always been at the top of my list. Because of the technical hold that I have on the tool, I always prefer Tableau. It would always be on top as compared to any other tool.

I work in the hospitality industry and I use Tableau Online and Tableau Bridge with our food ordering company. In our specific uses, I have found that Tableau is very good for extracting data, rather than for working live on the data.

Although the process of transferring data to Tableau isn't the best, once the data is already on Tableau, it works completely fine. I will typically make use of layer aggregation and other operations such as slicing and analyzing it by getting right inside the data in various ways.

Due to the demands of our industry, we always have things that we would like to see more in-depth over different dimensions, such as restaurants, branches, cities, and so on. With Tableau's help, our company can aggregate all the raw data and then analyze by rows, to see, for instance, which restaurant is doing the best by comparing them with one another. It also enables us to easily split areas into zones and use the data to test for not only which restaurants are doing the best, but also where (i.e. in which cities and branches). 

Although Tableau isn't the best for us when it comes to processing and working on live data, it is very good at extracting data for analysis. Once you have extracted the data, the aggregate layers you can create, along with slicing and other operations, are very handy. It allows us to really get inside the data, and it is, in my opinion, better than any other tool I have used with the same pricing model.

Of the best analysis features, multi-aggregation layers come out on top for me, because they let you extract raw details while making multiple aggregations on different time levels and different dimensions, and you still manage to get your work done quickly without having to load a lot of data grouped over different dimensions.

Tableau Bridge is also a very good tool, however I can tell that it does need a few fixes and some maintenance. That said, it's still good for its first few years since release.

Most of the problems in Tableau Online that I have noticed have to do with performance or weird, inexplicable bugs that I can't pin down. For example, you might try unloading some data, and you'll be waiting for a long time without anything happening.

These bugs always seem to happen when we perform big upgrades or do maintenance work, and we have had to send a lot of tickets for unexplained issues during these times. It doesn't seem to be a problem only for us, but also for customers all over the world, such as in Ireland, Western Europe, Eastern Europe, and the US, too.

As for future features, I would like to see major upgrades in Bridge and the Flow Tool, allowing us to do more data engineering work. I think it would give Tableau a big edge in the market to look into how to incorporate more data engineering tools into their product. 

Besides that, I would also like the charts to be more realistic and easier on the eyes.

I have been using Tableau Online for three years now.

The stability is okay. It's not 24/7, but you can say it's stable enough. In the start, it's more stable, especially compared to our OBIEE problems, which have taken two or three days to solve in the past.

It's easy to contact Tableau and ask to increase users or resources. They'll do it in the blink of an eye.

At present, we have 20 users, 12 of which are shift users. The majority of our users in total are board members or high-level managers. 

I wouldn't give their support more than a seven out of ten rating.

I have previously used Power BI, Qlik Sense, and Qlikview. I switched because Tableau was better in working with different sources compared to Power BI which was the only one that was truly on par. Qlik Sense and QlikView were easy to use but didn't have most of the features that Tableau and Power BI offered. Then there's OBIEE which I have used for the past two years, but it is quite difficult for non-technical users.

I also didn't like that Power BI is typically coupled with Microsoft Azure, whereas Tableau works well with AWS and Google which are a lot easier. 

The setup is straightforward. I mean, there's not much setup at all. It's easy for any mid-level user to do it. For example, I just used the documentation they provided and did everything myself. The documentation was sufficient
and the implementation strategy doesn't take more than 20 days.

I implemented Tableau by myself using the documentation they have made available. And for maintenance on one single node, you might need only two to three people involved.

For data extraction and analysis, Tableau is better than any other tool I have used with the same pricing model.

My ultimate advice is that you should know what the tool is capable of first and what your needs are. I think it's better to use the Server edition, and not Cloud, because there are a lot of problems in the Cloud version that don't seem to be present in the Server version. As for myself, I will likely switch to Tableau Server next year after doing a bit more research on how to do the changeover.

I would rate Tableau an eight out of ten.

We primarily use the solution for HR and energy dashboards. We have made and a few other dashboards for opportunities and accounts. 

Tableau has really good and interactive visualization and interactivity. 

The action feature which Tableau has is very useful for us. If we click on one visualization, it will pass the value to another visualization. That interactivity within different visualizations is the most valuable feature of Tableau.

Tableau would be really good if we could have predefined templates. I was doing a POC another newer tool, Einstein Analytics. They have predefined templates already set up. These predefined templates do the heavy lifting for the initial dashboards. We don't have to build them from scratch. Our dashboards look really good and 20 to 30% of the look and feel of the dashboard completes with the predefined templates. If Tableau works on the predefined templates, that would be so helpful to a lot of companies. It would save time for the developers.

The pricing is a bit higher than the competition. They'll need to lower it to stay competitive.

They need to move more into machine learning AI. Right now, in a POC that I'm doing with Einstein Analytics, they are more into machine learning and AI. Tableau is lagging as of now. If they want to have a long run in the market, they need to integrate machine learning and AI. It has to be very robust.

I've been using the solution for two years now.

I can say that this solution is quite scalable. I'd rate it eight out of ten. It integrates with many solutions. I haven't used our code in everything, however, I have used it for our HR integration and I find the code is quite scalable. 

In the last project I managed, there were 110 regular users of the solution with about 20 suer-users that were able to edit reports and dashboards and tasks of that nature.

I'd give technical support a nine out of ten. There were time zone differences. However, I got a timely reply and call from them, so it was very good. The support is very good. It's both responsive and helpful. I'm quite satisfied with them.

I've used BusinessObjects and MicroStrategy as well. I used to use Power BI for a few months.

The main competitor to this product is Power BI, which I also use. This license is a bit costly compared to Power BI. Not more, but a bit costly from what I've seen.

There's not much of a difference between Power BI and Tableau. They have the same kind of interface and the features. The main difference between the BusinessObjects and the others is that its an enterprise tool. The licensing cost of the BusinessObjects is very, very expensive. The visualizations and objects etc., all have separate licensing for dashboarding. On top of that, the chart's not that interactive. If you click on one chart, it will automatically change the data of the several other charts related to that. That is not very interactive compared to Tableau or Power BI.

The initial setup was not exactly straightforward. It was complex, or, to be fair, had a medium amount of complexity to it. The use cases were complex also and few of them had medium complexity to begin with.

Deployment was basically in the development environment and then we deployed it in the UAT for the users. They had a look at our reports in UAT first and then we deployed it into production. I was also working as a Tableau administrator also and then I learned Tableau administration in order to handle that aspect. I handled Tableau administration with the user and deployed the reports, etc.

The company has different verticals basically. I worked on HR and energy verticals. They also had finance and accounts. I have to maintain that administration part for all of them; not just my dashboards. From a deployment perspective, it was tough for me to maintain all the users and all the rules for the accounts department and for finance, and to be in the group for them, and to assign permissions for them. I did have issues in the servers in terms of gateways. I resolved them myself in the end with the help of Tableau support. 

I handled the implementation myself. I didn't need the assistance of a reseller or consultant.

The company chose to purchase a creator license for me, which was $70. With that license, you can also be an administrator. We also have 20-25 extra licenses and they cost around $20-$35 each. Those are for normal users who will be viewing the dashboards. Those are monthly charges.

There aren't any other costs over and above that.

Apart from that we had database licensing. So because we used Snowflake as a cloud database.

Our company has a partnership with Tableau.

I've used both on-premises and cloud, depending on the requirements.

This particular solution is quite an easy to use product. It's very robust. Even a layman who has previously was not worked with any other BI tools would love to work on this. They will find many things easier to implement. There are a few other tools that are in the market. However, from an implementation point of view, it's very robust. 

I'd rate the solution nine out of ten overall.

The primary use case is for household survey and population, and housing census analysis. I have also been using it for monitoring and evaluation of projects.

I provided Data Visualization skills to selected staff of The Gambia Bureau of Statistics (GBoS) in 2018 using Tableau. Previously, SPSS was used to analyze the data but after I introduced them to Tableau, the team was so happy that together we decided to look at the Census 2013 dataset and analyze it using Tableau.

I have also used it to develop a key indicator list based on the Living Standards Measurement Survey.

GBoS, with the help of the European Union, bought Tableau and have since been using it to analyze household surveys instead of SPSS or Stata, as they were doing before.

Another project that I am about to complete using Tableau is the Data Lifecycle Assessment of the Planting for Food and Jobs project in Ghana. I am working on this project with the Ministry of Monitoring and Evaluation and it is being sponsored by the Alliance for Green Revolution in Africa.

Already, the staff is so much in love with Tableau that they want me to provide Advanced Training for them so that they can adopt it as their Data Visualization Tool.

The most valuable features are the ability to classify variables into Dimensions and Measures, Ask Data, and Show Me.

The Dimensions and Measures feature solves one of the basic problems most would-be data analysts have, which is to determine which variables to analyze or focus on. Tableau makes this easy by splitting them into Dimensions and Measures and then use Dimensions to dissect or dice and slice the Measures.  

Ask Data enables non-technical personnel to quickly derive insights from data just by knowing which variables are available.

Show Me is a feature to help with knowing which chart is an appropriate one for the selected variables, and it makes helps in creating appropriate visuals.

I cannot end without mentioning the overall seamless flow of how to derive insights from data using Worksheets, Dashboards, and Stories.

I think predictive analytics is the main driver of business decisions and hence Tableau should strengthen the ability to make predictions.

The forecasting feature in Tableau in my view is too limited because it must have dates but I should be able to predict the outcome of an event without having a date as part of the input.

In situations where you are analyzing or using just one measure such as Sales, Tableau does not create the header for you. Furthermore, it is not straightforward as to how to create it.

I would like to have the ability to perform multiple pivots and creating different variables. For example, if I have the regional population for six regions and branch offices, together with the number of clients per branch, all as a record or observation, then I should be able to pivot them separately resulting in the Region, Population, Branch, and Clients.

I have been using Tableau for three years.

The scalability is simply awesome.

The technical support is awesome.

I have worked with Excel, SPSS, and Power BI.

Tableau is easy to use and the support from the community is awesome. Also, I see Tableau as a product for the future due to the commitment from the development team.

The Tableau Development Team listen to suggestions from the users and follow discussions on the community forum and factor that into product upgrades. 

End users want things to be done quickly and intuitively and the only way that any product will survive is by listening to end users 

The deployment was straightforward. I would say that it was a nice and easy, no-brainer setup.

The implementation was done in-house but there was an occasion that I had issues. I contacts support and it was super.

The ability to make insightful decisions quickly is a big benefit to all and therefore reduces cost in terms of manhours spent in cleaning and creating visuals.

It is a bit difficult for some people when they hear $70.00 per month, as some solutions are available for less than $10.00 or for free. What I always tell my trainees is that it is not so much about the cost, but rather, how you can quickly get the insights you have derived into the minds of your audience or stakeholders.

It is important to consider the ease of use. If a product is free but usability is a problem then it is not actually free because it cannot be even used.  

I had already used other tools and also wrote my own program in VBA to analyze data.

Customers need more insights and hence, they should look into Natural Language Processing (NLP). The ability to analyze text data or focus group discussions or radio phone-in programs would be helpful. 

When there is a major upgrade and you install it, it wipes off all of the recently used files and newbies get frustrated. If something can be done about it then that will be very helpful

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.