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ClearScape Analytics

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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 ClearScape Analytics?

ClearScape Analytics functions as Teradata's advanced analytics solution, incorporating robust, interconnected AI and machine learning features designed to deliver exceptional insights and faster results. This platform includes extensive in-database analytics that empower users to address complex problems with a diverse selection of analytic functions found directly within the database. It supports various programming languages and APIs, ensuring effortless compatibility with prominent open-source and partner AI/ML tools. With its "Bring Your Own Analytics" feature, companies can seamlessly integrate all their models, including those developed on different platforms. The ModelOps feature dramatically accelerates the time required to achieve value, reducing deployment timelines from months to mere days, while also facilitating automated model scoring for production environments. Additionally, it improves user abilities to swiftly leverage generative AI applications using open-source large language models, ultimately simplifying the overall analytics implementation process. This distinctive assemblage of functionalities equips organizations to maintain a competitive edge in the continually changing realm of data analytics, enabling them to adapt swiftly to new challenges and opportunities.