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Data Science
To develop and deploy effective AI systems, you need tools, techniques, and methodologies to hand data, build and evaluate models, and generate insights. Welcome to Data Science.

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Features

Building Trustworthy Data Foundations for AI

A plethora of reports highlight the prevalence and dangers of AI hallucinations and other forms of inaccuracies resulting from AI applications. These errors can be traced to many different root causes, but the solutions boil down to a few methods: restrict the content to a carefully defined and structured set of validated information, protect the application through governance and monitoring, and evaluate the output to provide continuous improvement.

Governing AI for Security, Compliance, and Trust: Who Gets to Grant AI Access?

Organizations are moving AI from isolated tasks into everyday operations. A tool that started out drafting emails or summarizing documents may soon be asked to search internal files, retrieve customer information, prepare transactions, route requests, or update records.

Powering AI Agents With RAG and Enterprise Knowledge

It should come as no surprise that AI has already infiltrated many parts of daily life. After all, AI has been around for decades. Still, some people are amazed to discover that things they take for granted, such as spellcheck, autocorrect, real-time traffic maps, spam filters, ride-hailing apps, and personalized music recommendations, are AI-enabled. The more that AI-enabled tools become embedded in daily routines, the less they seem to be advanced technology and more just a normal part of life. It's no longer magic, it's normal.

Enhancing AI Reasoning With Knowledge Graphs and GraphRAG

There is a disconnect happening with AI that cannot be ignored. A model can retrieve information, summarize it, or generate an answer, but it cannot determine whether the answer reflects how the business works or if it's truly correct. The limitation is not model intelligence but missing context. Using connected data, semantic relationships, and graph-based retrieval improves AI reasoning, contextual understanding, and decision making.

Enterprise AI Case Studies

Teradata Forwards Several Enterprise AI Customer Engagements Across Healthcare and Life Sciences

Teradata shows how healthcare and life sciences organizations are activating intelligence from their data and institutional knowledge at scale

Cleo and Bear Cognition Collaborate to Leverage AI-Driven Supply Chain Orchestration to Automate Business Process Workflows  

Cleo, a global leader in supply chain orchestration solutions through its Cleo Integration Cloud (CIC) platform, is partnering with Bear Cognition, Inc., a leading provider of automation and intelligence systems for supply chain operations.

Eletrobras Selects C3 AI to Scale Enterprise AI Across Latin America’s Largest Power Utility

C3 AI, the Enterprise AI application software company, announced a partnership with Eletrobras, Latin America's largest power and utility provider, to scale C3 AI Grid Intelligence for real-time fault monitoring and resolution across all of Eletrobras' operations centers.

Enterprise AI Whitepapers

Gartner Report: Critical Success Measures to Drive Your Customer Service AI Agent Strategy

The orchestration advantage: why platform architecture determines whether CX AI scales

MIT Technology Review Insights: The connected customer

On Demand Webinar: MIT Scaling Agentic AI Pilots