The Role of Data Quality in AI
Hosted by Chad Sanderson
What you'll learn
Understand the critical importance of data quality in AI
Learn how data quality is crucial for AI success, impacting decision-making and outcomes.
5 common data quality issues
Explore the 5 most frequent data quality problems that can derail AI projects
Enhance your data quality
Discover foundational strategies and best practices for improving your data quality
Why this topic matters
Data is the foundation of AI. Poor data leads to faulty models and unreliable results. Ensuring data quality isn't just about maintaining databases—it's about empowering your AI systems to deliver precise and actionable insights. In this lesson, you'll get a playbook of best practices and common pitfalls for data quality.
You'll learn from
Chad Sanderson
CEO of Gable.ai, seasoned data leader, and O'Reilly author
A prominent figure in the Data industry, having held key positions at leading companies such as Convoy, Microsoft, Sephora, Subway, and Oracle. He is also the author of the upcoming O'Reilly book, "Data Contracts," which is expected to make significant contributions to the field. Chad's diverse experience and innovative approach to data management have established him as a thought leader and a driving force in technology.
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