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support

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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 SLC is a Siemens software solution built to help organizations modernize analytics environments while continuing to use existing SAS language programs. It gives analysts, developers, and operations teams a flexible way to work with SAS language, Python, R, SQL, no-code tools, and drag-and-drop workflows in one ecosystem. The platform helps reduce migration risks by maintaining functionality for current SAS language applications while enabling gradual adoption of open-source analytics. Rapidminer SLC supports on-premises, cloud, and hybrid deployments, giving organizations more freedom to evolve infrastructure without disrupting business operations. Users can connect to a wide range of data sources, including cloud services, Hadoop, data warehouses, databases, Microsoft Excel, CSV files, SPSS, SAS language formats, and other file-based data. Its modern IDE allows teams to create, maintain, run, and analyze programs while reviewing data, results, and logs in one environment. Rapidminer SLC also makes it possible to exchange data between SAS language, Python, R, and SQL for more connected analytics development. Rapidminer SLC Hub adds enterprise management features for security, load balancing, publishing, deployment, and workload allocation. By combining legacy analytics support with modern open-source flexibility, Rapidminer SLC helps organizations improve productivity, scalability, and long-term analytics innovation.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Rapidminer
Rapidminer Knowledge Studio
Rapidminer Monarch
Rapidminer Panopticon

Integrations

Rapidminer
Rapidminer Knowledge Studio
Rapidminer Monarch
Rapidminer Panopticon

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/slc/

Product Features

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Predictive Analytics

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

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