Average Ratings 0 Ratings
Average Ratings 2 Ratings
Description
Modern Information Systems (ISs) accumulate vast quantities of data regarding the business processes they facilitate. This data serves as a foundation for process mining, enabling organizations to scrutinize their operational processes based on empirical evidence rather than assumptions. For instance, this can involve analyzing the workflow of a loan application at a bank or evaluating the patient care procedures in a hospital. Currently, there is a growing interest in process mining within both industry and academic settings. Consequently, the availability of various process mining tools is on the rise. Despite this growth, existing tools do not support the creation and execution of comprehensive analysis workflows that utilize multiple process mining algorithms. This limitation forces analysts to repetitively conduct process mining tasks by hand, making scientific experimentation in this area labor-intensive. To address this challenge, we have integrated RapidMiner, a platform that enables the design and execution of analysis workflows, with the ProM 6 process mining framework, thereby enhancing efficiency and effectiveness in process mining endeavors. This integration aims to streamline the analysis process, ultimately improving productivity for analysts in the field.
Description
Rapidminer Monarch is a Siemens self-service data preparation platform that enables business users and data teams to extract, clean, transform, and export data without coding. It is built to work with a wide range of sources, including complex PDFs, Excel files, spreadsheets, text reports, databases, and other enterprise systems. The software helps organizations convert unstructured or difficult-to-use information into structured data that can support reporting, analytics, machine learning, and business operations. Rapidminer Monarch is especially useful for teams that regularly reconcile reports, audit data, migrate legacy information, or prepare data from non-tabular files. Its no-code environment allows users to build repeatable workflows through drag-and-drop tools, reducing dependence on manual cleanup and IT support. The platform increases trust by maintaining data lineage, reconciliation configuration, and change histories for every transformation. Users can also access thousands of pre-built apps for systems such as ADP, Dayforce, Fiserv, Visa, Meditech, and SAP. Rapidminer Monarch Server helps centralize, govern, and operationalize data preparation workflows for enterprise-scale deployments. By automating repetitive preparation tasks, Rapidminer Monarch helps teams improve accuracy, speed up analytics, and make better use of data from across the business.
API Access
Has API
API Access
Has API
Integrations
Rapidminer
Rapidminer Knowledge Studio
Rapidminer Panopticon
Rapidminer SLC
Vertica
Integrations
Rapidminer
Rapidminer Knowledge Studio
Rapidminer Panopticon
Rapidminer SLC
Vertica
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
ProM
Founded
2010
Country
Netherlands
Website
www.promtools.org/doku.php
Vendor Details
Company Name
Siemens
Founded
1847
Country
Germany
Website
www.siemens.com/en-us/products/rapidminer/monarch/
Product Features
Product Features
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control