Data Chats Podcast

Bridging the Gap Between Data Science and Business

Nov 17, 2023

Renowned expert Eric Siegel discusses bridging the gap between data science and business. Key topics include aligning with business objectives, measuring deployment success, and the importance of human involvement in AI. Siegel's insights offer a roadmap for organizations seeking to leverage the power of AI in driving their business forward.

50:36

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Episode guests

Eric Siegel

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Episode notes

Podcast summary created with Snipd AI

Quick takeaways

Success in machine learning projects relies on clear alignment with business objectives.

Measuring deployment success requires defining impactful metrics reflecting business impact.

Human involvement is indispensable alongside AI to validate results and ensure business value realization.

Deep dives

The Importance of Capturing Business Value in Machine Learning Projects

Machine learning projects often face challenges in capturing actual business value, despite the high expectations. Organizations need to shift focus towards successful deployment and integration of machine learning models to drive real business impact. Assimilating core technology with organizational objectives is crucial for maximizing the benefits.

Introduction

2min

Bridging the Gap Between Data Science and Business with BizML

18min

Navigating Change Management in Machine Learning Projects: A UPS Case Study

6min

Deploying Data-Driven Solutions in Businesses

4min

Navigating Realities of AI and Business Integration

18min

Exploring the Future of Data Science Roles in Organizations

3min

"There's a gap between the technical side and the business side. You need to bridge that gap with a common understanding of what's predicted, how well, and what's done about it."

– Eric Siegel

In this insightful Data Chats episode, we explore the critical intersection of business and machine learning with Eric Siegel, a renowned expert in the field. Eric’s insights offer a roadmap for organizations seeking to leverage the power of AI to drive their business forward.

Eric Siegel is the founder of Machine Learning Week, former Columbia professor, and bestselling author of his new release, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.” He has a talent for bridging the gap between complex data science concepts and the practical application of machine learning in the business world.

Check out Eric’s new release, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment” here.

With his remarkable insights, Eric Siegel sits down with host, Chris Richardson, as he guides us through the exciting yet challenging landscape of AI's role in business. They discuss:

Aligning with Business Objectives: Success comes from defining clear goals and understanding how AI can contribute to achieving them.
Measuring Deployment Success: Companies must define meaningful metrics that reflect the project's impact on the business.
Human Involvement: While AI and ML hold great potential, there’s still a need for human involvement to validate AI-generated results and maintain quality control.
New Roles and Responsibilities: As AI's role in business continues to evolve, new job titles and roles, such as machine learning business liaisons, are emerging.

Want to learn more from Eric? Tune in to his previous interview with us here.

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