Likelihood to Recommend MATLAB really does best for solving computational problems in math and engineering. Especially when you have to use a lot of functions in your solving process, or if you have a nonlinear equation that must be iteratively solved. [MATLAB] can also perform things like integration and derivation on your equations that you put into it.
Read full review Tableau Desktop is one the finest tool available in the market with such a wide range of capabilities in its suite that makes it easy to generate insights. Further, if optimally designed, then its reports are fairly simple to understand, yet capable enough to make changes at the required levels. One can create a variety of visualizations as required by the business or the clients. The data pipelines in the backend are very robust. The tableau desktop also provides options to develop the reports in developer mode, which is one of the finest features to embed and execute even the most complex possible logic. It's easier to operate, simple to navigate, and fluent to understand by the users.
Read full review Pros It has a very user friendly library which helps users learn this software fairly quickly in a short span of time. The graphical user interface provided by the software is really good. The code that a person writes allows options for debugging. One can visualize the flow of control of their code inside MATLAB. Read full review An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization. Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community. Read full review Cons MatLab is pricier than most of its competitors and because of this reason, many organizations are moving towards cheaper alternatives - mostly Python. MatLab is inefficient when it comes to performing a large number of iterations. It gets laggy and often crashes. Python is better in this regard. There is a limited number of hardware options (mostly NI) that can be connected directly to the data acquisition toolbox. Read full review Formatting the data to work correctly in graphical presentations can be time consuming Daily data extracts can run slowly depending on how much data is required and the source of the data The desktop version is required for advanced functionality, editing on [the] Tableau server allows only limited features Read full review Likelihood to Renew Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.
Read full review Usability MATLAB is pretty easy to use. You can extend its capabilities using the programming interface. Very flexible capabilities when it comes to graphical presentation of your data (so many different kinds of options for your plotting needs). Anytime you are working with large data sets, or with matrices, MATLAB is likely to be very helpful.
Read full review Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
Read full review Reliability and Availability When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Read full review Performance Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
Read full review Support Rating The built-in search engine is not as performing as I wish it would be. However, the YouTube channel has a vast library of informative video that can help understanding the software. Also, many other software have a nice bridge into MATLAB, which makes it very versatile. Overall, the support for MATLAB is good.
Read full review I have never really used support much, to be honest. I think the support is not as user-friendly to search and use it. I did have an encounter with them once and it required a bit of going back and forth for licensing before reaching a resolution. They did solve my issue though
Read full review In-Person Training It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
Read full review Online Training The training for new users are quite good because it covers topic wise training and the best part was that it also had video tutorials which are very helpful
Read full review Implementation Rating Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.
David Fickes Decision Sciences - Modeling, Simulation & Analysis
Read full review Alternatives Considered How MATLAB compares to its competition or similar open access tools like R (programming language) or SciLab is that it's simply more powerful and capable. It embraces a wider spectrum of possibilities for far more fields than any other environment. R, for example, is intended primarily for the area of statistical computing. SciLab, on the other hand, is a similar open access tool that falls very short in its computing capabilities. It's much slower when running larger scripts and isn't documented or supported nearly as well as MATLAB.
Read full review If we do not have legacy tools which have already been set up, I would switch the visualization method to open source software via
PyCharm ,
Atom , and
Visual Studio IDE . These IDEs cannot directly help you to visualize the data but you can use many python packages to do so through these IDEs.
Read full review Scalability Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
Read full review Return on Investment MATLAB helps us quickly sort through large sets of data because we keep the same script each time we run an analyzation, making it very efficient to run this whole process. The software makes it super easy for us to create plots that we can then show to investors or clients to display our data. We are also looking to create an app for our product, and we will not be able to do that on MATLAB, therefore creating a limiting issue and a new learning curve for a programming language. Read full review Tableau was acquired years ago, and has provided good value with the content created. Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace. Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies. Read full review ScreenShots