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公式動画＆関連する動画 [Retail AI: Dynamic Price Markdown Demo]
See how Oracle AI Data Platform helps retailers optimize inventory, improve sales velocity, and increase margin with Enterprise AI, machine learning, and AI agents. Explore how Oracle AI Data Platform unifies data engineering, data science, and AI-driven decision intelligence for faster retail operations at https://social.ora.cl/6005BD0aQP
See how Oracle AI Data Platform helps retailers improve inventory management and sales velocity with AI-driven dynamic price markdowns. In this demonstration, a planning manager identifies stale inventory, evaluates pricing recommendations, and prioritizes markdown opportunities while balancing profitability and revenue goals. AI-powered recommendations help teams quickly identify products that require action and make more informed pricing decisions.
The demonstration also shows how Oracle AI Data Platform supports the complete Enterprise AI workflow. A data engineer builds zero-copy data pipelines across the AI Lakehouse, transactional systems, and customer purchase data using notebooks and Medallion architecture. Automated pipeline orchestration monitors workflow health and uses AI-assisted tools to help resolve issues quickly. A data scientist develops regression models with PySpark and open-source libraries on Spark compute clusters, while an AI developer configures, tests, and deploys AI agents using trusted machine learning predictions and enterprise data.
Together, these capabilities help retailers unify data engineering, machine learning, and AI agents to improve inventory decisions, maximize margins, and accelerate operational efficiency.
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