Datawatch Monarch/Modeler and RMS: Very effective for data mining from legacy reports.
September 12, 2014

Datawatch Monarch/Modeler and RMS: Very effective for data mining from legacy reports.

Frank Pappalardo | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Software Version

Monarch (multiple versions) and RMS

Overall Satisfaction with Datawatch

Some end users and data analysts in our organization use Datawatch Monarch to extract data from mainframe reports. We also have Datawatch Monarch RMS running on our IBM Content Manager On Demand (CMOD) report distribution platform, which allows users to extract their data without running Monarch themselves.
  • Creating a basic model to extract data from a report is very easy.
  • Advanced features like Calculated Fields and External Lookups allow you to augment the raw data.
  • You can create a "project" to automate the data extraction. Combined with Datapump (a separate DW app), you can fully automate the process once the raw report is generated.
  • Moving fields around in a model can be very cumbersome because you can't overlay them.
  • Moving models between different versions of Monarch can be a pain.
  • I'd love to see a utility that would combine the field lists from a collection of models. This would help us standardize our field definitions.
We are generally very pleased with the product, and it is pretty well entrenched in our organization. No major changes in reporting delivery are in the works.
* 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" (