Behind the Data with CloverDX

The challenges of implementing AI in data systems

CloverDX Season 1 Episode 5

In this episode of Behind the Data, host Matthew Stibbe speaks with Andy Coulson, a cloud architect at Epicor, about the emerging trends in data engineering, particularly the integration of AI and machine learning. They discuss the challenges of implementing AI in data systems, the transformation of Epicore's auto catalog, and the architectural decisions behind it. Andy shares insights on data management, the importance of understanding data volumes, and lessons learned from data integration projects, including the need for foresight in planning.

Takeaways

  • AI and machine learning are transforming data engineering.
  • Prompt engineering is crucial for effective AI integration.
  • Epicore is moving towards a cloud-native architecture.
  • Graph databases offer unique advantages for data relationships.
  • User experience is a key consideration in AI applications.
  • Data normalization is essential for effective data management.
  • Understanding data volumes is critical for performance.
  • Iterative development has its place, but so does rigorous planning.
  • Collaboration with domain experts enhances project success.
  • Foresight in data integration can prevent future challenges.

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Hosted by Matthew Stibbe from Articulate Marketing

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