Quantrix vs. Tableau Desktop

If you find yourself in the ocean of traditional spreadsheets, overwhelmed by broken links, errors, model audit problems, hardwiring, etc. here is a lifebuoy for you. If you want to have full flexibility in your budgeting and forecasting in contrast to ERPs with rigid structures and one-size-fits-all concept. If you are small or medium size company and do not want to invest in costly enterprise solutions. If you need a fast implementation https://youtu.be/5W_q5Xhw5fg

The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).

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• Building complex financial planning model availing of a multidimensional data structure coupled with a powerful formula language, with the immediacy and intuitiveness typical of spreadsheets
• Implement quickly model modifications (new products, new scenarios, new time periods) simply adding new "items" to "categories" (corresponding to dimensions in a multidimensional data model)
• Scale up models to very large datasets with very fast computation times
• Easily import data from text files, other Quantrix models and external databases via DataLink and DataNAV
• Save snapshots of tables computed in Quantrix to external databases via DataPush

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• 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.

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• Hard to be critical of the Quantrix team as I know they strive to produce the best product possible. I suppose the next thing on my wish list would be the application of the new Solver functionality to be available in the Qloud.
• A big help for new users would be a good book on transitioning from Excel or other environment into Quantrix. I know first hand it can be difficult to transition when having to learn the program through a help guide, forums and tech support. I had a lot of trial and error in my journey to producing the desired models. On one hand it was a valuable method as it taught me a lot of what not to do, but I will admit it was not the most efficient way to do things.
• Would also love to see local user groups being formed at some point in the future. Quantrix puts on a fantastic conference once a year in beautiful Maine, but it is a big journey for someone in Southern California (and limited to one or two days a year). I would like to see some local chapters formed in different areas of the country so local Quantrix users can get together more often and collaborate (maybe a quarterly or semi-annual meetup?). Our Quantrix community is still relatively small and may be a difficult task for some areas, but is also the very reason why this would be great idea.

• Pricing should be more user-friendly and usage-driven
• Making edits to the production reports is fairly tough and has a vast scope of additional capabilities
• Tableau Desktop should be able to differentiate itself from the Tableau server else there is no major meaning of two different products being offered

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.

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For a newbie it can be difficult until you get the hang of the system. Quantrix is a very logical system, once you understand its underlying ideas.

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.

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.

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

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Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.

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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.

I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems

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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.

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Overall, I was not part of the ultimate decision to purchase Quantrix. I terms of user-friendliess and robust reporting capabilities I do think Tableau has Quantrix outclassed. That being said, Quantrix does provide more in-depth analyses for our relevant data and provides better modeling for our forecasts out of the box. The accuracy of the tools output is also much better

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I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.

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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.

• Capacity forecasting used to take hours to calculate with a ton of manual modifications. Quantrix has automated that so a model can be updated at any time with a click of a button
• The accuracy of the models is incredible. It took some tweaking to add in data scubbers, but now it runs almost flawlessly
• The confidence the management teams have in the output of the model is amazing. Before, people would question the output, have you rebuild it, and then compare. Now the report comes out and the output has high confidence.

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• 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.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info