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Harnessing the Power of Enterprise Knowledge Graphs for AI and Analytics

Harnessing the Power of Enterprise Knowledge Graphs for AI and Analytics

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 This episode features Siemens veterans John Nixon and Bill Hahn, along with Ben Szekely coming from the Altair family (now part of Siemens). They discuss how Altair's RapidMiner platform fits into Siemens' portfolio and the broader AI and data ecosystem. Key points: RapidMiner provides a low-code platform for machine learning and data analytics, helping a wide range of users deploy AI models quickly. RapidMiner also includes enterprise knowledge graph capabilities, which allow companies to integrate and contextualize diverse data sources without having to move all the data into a centralized platform. The knowledge graph creates a virtual "blanket" over a company's existing data systems, automatically mapping relationships between data points from different sources (e.g. linking maintenance records to asset performance data). This contextualized data provides a stronger foundation for AI models, which tend to perform better with rich, interconnected data versus just accessing a data lake. RapidMiner enables faster time-to-value compared to traditional approaches of manually integrating data or building a monolithic data warehouse. A key use case is in maintenance and operations, where RapidMiner can quickly pull together all relevant data about an asset (from manuals to sensor data) to empower field technicians and engineers. Overall, the discussion highlights how RapidMiner's capabilities around data integration, knowledge graphs, and low-code AI can help Siemens customers accelerate their digital transformation and get more value from their existing data and systems.
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