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Data engineering is the backbone of AI systems. After all, the success of AI models heavily depends on the volume, structure, and quality of the data that they rely upon to produce results. With proper tools and practices in place, data engineering can address a number of common challenges that organizations face in deploying and scaling effective AI usage.
Join this October 15th webinar to learn how to:
- Quickly integrate data from multiple sources across different environments
- Build scalable and efficient data pipelines that can handle large, complex workloads
- Ensure that high-quality, relevant data is fed into AI systems
- Enhance the performance of AI models with optimized and meaningful input data
- Maintain robust data governance, compliance, and security measures
- Support real-time AI applications
Reserve your seat today to dive into these issues with our special expert panel.
Register Now to attend the webinar Data Engineering Best Practices for AI. Don't miss this live event on Tuesday, October 15th, 11:00 AM PT / 2:00 PM ET.
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MODERATOR |
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Brian Leonard
Director of Engineering
Airbyte |
Tim Spann
Principal Developer
Advocate, Milvus
Zilliz |
Stephen Faig
Research Director
Unisphere Research
and DBTA |
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