Altair Monarch vs. Dataiku

* Individual seat licenses are very expensive, which is one reason we are moving to CMOD/RMS. But RMS has less functionality than standalone Monarch (now known as "Modeler"). I would like to know what improvements we can expect in RMS, I would also ask, what is the future of the standalone version? * In the past there has been a dearth of user discussion and support in the online community, although this seems to be improving with the new "Datawatch Commmunity" (http://community.datawatch.com).

Incentivized

Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.

Incentivized

• It allows us to quickly dump large non-ALV SAP reports into Excel. Exporting these reports prior to Modeler was cumbersome at best.
• Customizable models allow us to easily gather required data from the same report running different dates. This is perfect for month-end reports.
• Quick exports.

Incentivized

• Low-code platform.
• Open source version includes most valuable modules.
• User friendly documentation.

Incentivized

• Setting up visualizations with time series data requires a good understanding of how the software works. I would like it to be more intuitive. Having said that, time series data is inherently complicated and I don't see any obvious ways to make it simpler. But I'm not a software designer myself; they could put more resources into the user experience.
• Their video training is really helpful and they have a big library of videos, but the videos get out of date as they come out with new versions. I can imagine that it's difficult to keep all the videos updated, but it would be great if the videos were always using the latest major version of the product.
• They need more visualizations. They have a pretty big collection now but it seems like there is often some other way to present and visually analyze data that would be a better/tighter fit with requirements than the visualizations available in the standard product. I understand it is possible to add more visualizations - custom visualizations - but that's beyond my expertise.

Incentivized

• The visualization feature of flow still has a lot room to improve, when the flow is complex.
• The "non-coding" template/building block for deep learning lack of many important configurable parameters.
• Lack of the unified way to allow applying the "design pattern" on the Python codes (if we want to develop our own module or building blocks.

Incentivized

Datawatch recently repositioned Data Pump and essentially priced us out of the market. The initial investment was very inexpensive, but the yearly maintenance contract was viewed as being a little pricey. The only value of the contract was that it included software upgrades. The Professional Services portion of the contract that was meant to provide support was not viewed as being very effective or beneficial.

Incentivized

The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level

Incentivized

The amazing part of Dataiku DSS is their customer service. Based on urgency and technical level, you get a reply from the Dataiku engineer when you raise a query. So far, my queries have been pretty complex to solve, so I have received solutions even from the CTO of the company as well, which is why I would describe their customer support as very good.

Incentivized

Datawatch is very good value of money compared to QlikView; QlikView is really more of a BI tool and has a lot of functions that I didn't need. Datawatch is very strong in the real-time area where Tableau, Panorama, and Qlik don't do very well. If you need to set up a visual monitoring dashboard, Datawatch is the best product I've seen for that. if you want to do a lot of in depth statistical analysis of large databases, Tableau is probably a good option.

Incentivized

Dataiku was selected for me, but I am happy about that. I like Dataiku for the user experience, it feels less code-y and I like to demo things to non technical stakeholders because they can still follow along. When you open some other notebooks, you can see that peoples eyes start to glaze over

Incentivized

• Data Pump reduces complexity of report solutions by offering a standardized approach for organizing and scheduling
• 97% service level for past 5 years for all of our jobs going through Data Pump

Incentivized

• So far it has had a positive impact. Multiple departments are coming to us with their business problems.
• I can't specifically say about ROI as I'm a developer, though I have heard this solution is economical compared to other AI/ML enterprise tools.
• By using this tool, my client has let go of software that was used earlier, and we have created a simpler framework to replace that software.

Incentivized