How Data Platforms Affect Machine Learning and Artificial Intelligence - MLOps Podcast

Explore the critical role of data platforms in machine learning and artificial intelligence in this 39-minute podcast episode featuring Jake Watson, Principal Data Engineer at The Oakland Group. Gain insights into common patterns in data platforms, the organizational aspects of data mesh, recommended structural design patterns, and the importance of data modeling. Learn how to deal with data sprawl, ensure data quality, and understand the data hierarchy when building a platform. Discover strategies for integrating AI and ML into existing data platforms, structuring ML platform teams, and leveraging existing solutions. Delve into the synergy between data pipelines and AI/ML applications, and understand why solid data foundations are crucial for successful AI and ML implementations.

[] Jake's preferred coffee
[] AI in Production Conference teaser
[] Takeaways
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[] Data Engineer's Crucial Role
[] Jake's background
[] Data Platform Foundations blog
[] Day-to-day common patterns in a platform
[] Data mesh organizational side of things
[] Data platform structural design patterns for recommendation
[] Importance of data modeling
[] Dealing with the sprawl
[] Data quality
[] Data hierarchy on building a platform
[] Bolstering AI ML on top of a platform
[] ML Platform Team Structure
[] Don't reinvent the wheel
[] Data pipelines synergy
[] Wrap up