Nintex offers a platform that helps companies discover, automate, and optimize business processes.
$480
Minimum 1,000 users per user
Tableau Desktop
Score 8.3 out of 10
N/A
Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
Nintex Process Platform is much easier to begin with as low code or no code tool, which reduced amount of time and effort to learn and we can start working on it within a few weeks after taking the training session with Nintex. We can build the same application with same …
The Nintex K2 platform is not only efficient and developer-friendly, but the support provided by the vendor is also highly commendable. The platform's ease of use and robust functionality make it a preferred choice for developers, while the vendor's exceptional support ensures smooth implementation and ongoing assistance, enhancing overall user satisfaction.
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).
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.
Adding Machine learning features like the "Image and Text Automation" component, which allows bots to extract data from unstructured sources like scanned documents or PDFs.
Natural language processing (NLP) features to understand and interpret human language, which can be useful for tasks like customer service or data entry. mostly for middle east countries where Arabic language is used.
Integration with external systems where many industries uses their own legacy systems and they need RPA bot to interact with their systems as well.
Adding More OCR tools for Document data extraction and dynamic content.
We are currently investigating which collaboration platform best suits our needs. Chances are that we move to SharePoint Online and then we're going to also consider the microsoft power platform (power automate and power apps) to develop forms and workflows. Aspecially the pricing model for the cloud is currently a blocking factor to go for the Nintex solution in the Cloud.
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.
Based on the on-prem experience with this tool, I believe that they have a lot of potential to help the online version catch up to where the on-prem left off. Nintex developed their online version and it is not as fully formed or capable compared to the on-prem version, and the licensing model scales back what we would have liked to be an expansion or at least continuous improvement of existing flows. It is also not near as user friendly specifically to non-developers and has an uncanny similarity to Microsoft Flow in the online instance. Consistent with my reviews of the tool - I believe they have some good approaches to design thinking that, if translated well from on-prem to online, could make this a clear winner again.
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.
The Nintex Process Platform has never crashed or had any availability issues during my usage. However there was an issue that was of my own making that caused a slowdown of the system. I had set up a process to run once a day and check for employees on a list that had certain parameters selected, and for some reason that I had to troubleshoot, the process instead ran constantly, which filled the cache quickly. I ended up having to dismantle that process so the system didn't crash.
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.
Unlike any other process automation product out there. Not only is it a low-code, easy to use tool for building processes in environments like SharePoint or Salesforce, they have really started to expand their tool-set by offering tools to manage other things like process mapping, RPA, mobile,etc.
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
The support team works as fast as they can and they are usually fast to solver the issues. Sometimes they need more time to solve one of them because our workflows and so on are more complex than usual clients.
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.
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 used the Nintex training software, it was easy to watch and follow along. It didn't go too fast and was descriptive enough to understand what the steps needed were in order to produce efficient workflows and user friendly forms.
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
1.Start with Simple Workflows: Begin with basic workflows to gain user confidence before tackling complex processes. 2.Involve Stakeholders Early: Engage business users and IT early to align workflows with real business needs. 3.Comprehensive Training: Invest in user training to ensure smooth adoption and reduce resistance. 4.Leverage Prebuilt Templates: Use Nintex’s templates to speed up implementation and maintain consistency. 5.Iterate and Optimize: Continuously improve workflows based on user feedback and performance metrics.
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.
Microsoft environment does not have the scalability of Nintex; it is perfect for small and medium-sized companies, especially in environments where Microsoft environment is almost entirely used. Although Microsoft offers options to connect to other applications, its platform lacks the development and robustness that Nintex provides. Nintex not only covers Microsoft environments but also Google and other important platforms.
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.
The scalability is really bottlenecked by the imagination of the user. I was able to make processes for my own personal usage, making my daily tasks easier. I was also able to make processes that affected hundreds of employees, making large standardization and efficiency gains. So either way, the system is used the same way, and I was the limiting factor.
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.
People have woken up to the amount of overlap after mapping their processes.
People can be resistant to process changes. You need to have the support from above or support from the 'business' that you are process changing to be able to see the positive impacts.
Numbers talk. if you can get a general salary figure from your HR dept to show savings for 'employee bands', then when you present reports, they will be all the richer in data.
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.
