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What is Rapidminer SLC?

Rapidminer SLC is a Siemens analytics platform designed to help organizations modernize SAS language environments while expanding into open-source and multi-platform analytics. It allows teams to keep using existing SAS language programs while also working with Python, R, SQL, no-code tools, and drag-and-drop workflows. The solution helps organizations reduce migration risk by supporting existing analytics assets rather than requiring a disruptive replacement process. Rapidminer SLC is built to maintain business continuity while giving analysts, developers, and operations teams a path toward a more flexible analytics ecosystem. Users can create, execute, and operationalize analytics in modern environments across on-premises, cloud, and hybrid infrastructures. The platform supports access to many data sources, including cloud services, Hadoop, data warehouses, databases, Microsoft Excel, CSV, SPSS, SAS language data, and other file-based formats. Its Analytics Workbench provides a modern IDE for building, maintaining, running, and reviewing programs across multiple languages. Teams can explore data, results, and logs using code, no-code methods, or a combination of both. Rapidminer SLC makes it easier to exchange data between SAS language, Python, R, and SQL, helping organizations blend established workflows with newer analytics approaches. Rapidminer SLC Hub supports enterprise needs such as security, load balancing, deployment, publishing, scheduling, user provisioning, and workload distribution across resilient node clusters. With broad data access, multi-language development, centralized governance, and enterprise execution tools, Rapidminer SLC helps businesses transition analytics infrastructure while protecting existing investments.

What is NAVIK AI Platform?

An advanced analytics software solution is crafted to enable leaders across sales, marketing, technology, and operations to make well-informed business choices through comprehensive data insights. It addresses a diverse range of AI needs, which include data infrastructure, engineering, and analytics. The interface, workflows, and proprietary algorithms are specifically customized to align with the unique requirements of each client. With modular components, it facilitates tailored configurations, enhancing its adaptability. This platform not only aids in decision-making processes but also automates them, reducing human biases and leading to better business results. The remarkable increase in AI adoption necessitates that companies deploy strategies capable of rapid scaling to maintain their competitive advantage. By merging these four distinctive capabilities, organizations can realize substantial and scalable impacts on their business effectively. Adopting such innovations is crucial for driving future growth and ensuring long-term sustainability in an ever-evolving market landscape. As businesses continue to navigate this landscape, leveraging advanced analytics will become increasingly vital for success.

Media

Media

Integrations Supported

Rapidminer
Rapidminer Knowledge Studio
Rapidminer Monarch
Rapidminer Panopticon

Integrations Supported

NAVIK MarketingAI
NAVIK SalesAI

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Android

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Siemens

Date Founded

1847

Company Location

Germany

Company Website

www.siemens.com/en-us/products/rapidminer/slc/

Company Facts

Organization Name

Absolutdata Analytics

Date Founded

2001

Company Location

United States

Company Website

www.absolutdata.com

Categories and Features

Data Analysis

Not specified

Data Mining

Not specified

Machine Learning

Not specified

Predictive Analytics

Not specified

Categories and Features

Data Engineering

Not specified

Machine Learning

Not specified

Predictive Analytics

Not specified

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