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What is RapidProM?

Contemporary Information Systems (ISs) gather extensive data related to the business operations they support. This data acts as a crucial basis for process mining, allowing organizations to examine their operational workflows through concrete evidence instead of mere conjectures. For example, one might investigate the progression of a loan application in a banking institution or assess the procedures for patient care within a healthcare facility. Currently, there is an increasing fascination with process mining across both corporate and academic realms. As a result, the number of available process mining tools continues to expand. However, many of these tools fall short in providing the ability to create and implement comprehensive analysis workflows that leverage multiple process mining algorithms. This shortcoming compels analysts to repetitively perform process mining tasks manually, rendering scientific exploration in this domain quite labor-intensive. To overcome this issue, we have successfully integrated RapidMiner, a platform that facilitates the design and execution of analysis workflows, with the ProM 6 process mining framework. This integration not only boosts efficiency and effectiveness in process mining activities but also aspires to significantly enhance the productivity of analysts working in this field. As the demand for streamlined processes grows, the combination of these powerful tools could set a new standard in the realm of data analysis.

What is IBM Process Mining?

IBM Process Mining empowers organizations to uncover business processes that stand to gain significantly from automation opportunities. By leveraging data from business systems, it constructs comprehensive process visualizations that highlight potential bottlenecks or deviations that might be obscured within existing workflows. This tool provides users with an unbiased perspective on their business operations, pinpointing specific areas where automation efforts should be concentrated. Additionally, it enables the simulation of various scenarios to effectively prioritize automation projects based on their potential impact. As a core component of IBM Cloud Paks for Automation, IBM Process Mining not only identifies the most promising processes for automation but also assesses the anticipated return on investment. Furthermore, it illustrates the potential effects of automation initiatives throughout the workflow, allowing for informed decision-making prior to implementation. This ability to foresee changes enhances strategic planning and optimizes resource allocation in automation endeavors.

Media

Media

Integrations Supported

Automation Anywhere
Qlik Cloud Analytics
RapidMiner

Integrations Supported

Automation Anywhere
Qlik Cloud Analytics
RapidMiner

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ProM

Date Founded

2010

Company Location

Netherlands

Company Website

www.promtools.org/doku.php

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/cloud-pak-for-business-automation/process-mining

Categories and Features

Categories and Features

Business Process Management

Access Controls / Permissions
Alerts / Notifications
Business Process Automation
Business Rules Management
Collaboration
Process Change Tracking
Process Mapping
Process Modeling & Design
Visual Workflow Management

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