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

I would recommend it because it's an amazing tool for different levels of users. From Business Analysts to Data Scientists to Managers, various employees can make use of this tool to make data-driven decisions. I'm not sure about where it would be less appropriate as I'm using it as Data Scientist and so far it pretty much caters to my need.

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

• Very intuitive and easy to use UI, making a lot of types of users can collaborate with each other easily, by visualizing the same workflow.
• Many building blocks can be reused immediately, avoid a lot of non-standard boiler plate implementation.
• Data pre-analysis and feature engineering assistance increase the productivity as well as the efficiency of data scientists.
• Many data connectors support wide range of data storage, from SQL, TeraData, Hadoop Hive, etc.
• Support from research till final MaaS solution deployment.

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• Their video training is really helpful and they have a big library of videos, but the videos get out of date as they come out with new versions.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

• Its community support is very limited at the moment
• Complex to integrate with automation tools such as Blue Prism

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

As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.

Incentivized

The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.

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

Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.

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

• Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
• Platform also ease tracking of data processing workflow, unlike Excel.
• Build-in data visualizations covers many use cases with minimal customization; time saver.

Incentivized