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How to Accelerate AI-Driven Decision Intelligence with Smart Data Fabric

How to Accelerate AI-Driven Decision Intelligence with Smart Data Fabric

SupplyChainBrain Webinar

Increasing operational costs, labor shortages, and geopolitical tensions are keenly felt by supply chain organizations and highlight the importance of fast, informed decision-making.

Learn how a smart data fabric can be used to unify data across disparate sources and accelerate AI-driven decision intelligence. We'll delve into real-world use cases showing how this approach can be used to leverage real-time predictive and prescriptive analytics, as well as generative AI, to optimize your supply chain operations.

A smart data fabric can help organizations attain an agile supply chain with integrated decision intelligence.

What you will take away:

InterSystems Smart Data Fabric for consistent unified data
Super charged problem solving with Data Fabrics and Generative AI
Accelerated business value to LOB (Line of Business) with decision intelligence

How to Accelerate AI-Driven Decision Intelligence with Smart Data Fabric

Speakers:
Mark Holmes, Senior Advisor for Supply Chain, InterSystems
Ming Zhou, Head of Supply Chain Strategy, InterSystems

Moderator:
Robert Bowman, Editor-in-Chief, SupplyChainBrain

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Eleven common questions and answers

Today more than ever before, organizations are striving to gain a competitive edge, deliver more value to customers,reduce risk, and respond more quickly to the needs of the business. To achieve these goals, organizations need easy access to a single view of accurate, consistent, and trusted data – and all in real time. However, growing volumes and complexities of data make this difficult to achieve in practice. As data grows, so does the prevalence of data silos, making integrating and leveraging data from internal and external data sources a challenge.

Bloor InPerspective Brief

In today’s global marketplace, supply chain management plays a pivotal role in the success of businesses across various industries and, with the increasing complexity and interconnectedness of supply chain networks, the demand for efficient and effective solutions continues to rise.

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