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Joe Reis

Speaker

Joe Reis

3

talks

Joe Reis is a data professional with 20 years in the data industry, known as a "recovering data scientist" and a business-minded data nerd. His experience spans statistical modeling, forecasting, machine learning, data engineering, and data architecture. He is the co-author of Fundamentals of Data Engineering (O'Reilly, 2022).

Bio from: Small Data SF 2025

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Talks & appearances

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Face To Face
with Taylor McGrath (Boomi) , Chris Tabb (LEIT DATA) , Joe Reis (DeepLearning.AI)

6:00 pm - Intro & Drinks hosted by Chris Tabb

6:10 pm - Session One - High Performance Data Products

David Richardson, Jon Cooke, Taylor McGrath, Mark van der Heijden

6:30pm - Session Two - High Performance Data Models

Joe Reis 🤓, Keith Belanger, Nick White, Eevamaija Virtanen

6:50pm - Pizza and Drinks 🍕🥤🍷🍻

7:00pm - Session Three - High Performance AI

Alex Chung, Jai Parmar, Sonny Rivera, Addie McNamara

7:20pm - Town Hall Debate

Sponsors: Coalesce, LEIT DATA, Rivery, SqlDBM, ThoughtSpot 

In an era where data drives decision-making and innovation, data engineering stands at the forefront of technological advancement. 

This panel brings together leading experts; Chad Sanderson, Joe Reiss, Sarah Levy and Pushkar Garg to explore the critical challenges and opportunities shaping the field today.

For decades, data modeling has been fragmented by use cases: applications, analytics, and machine learning/AI. This leads to data siloing and “throwing data over the wall.”

With the emergence of AI, streaming data, and “shifting left" are changing data modeling, these siloed approaches are insufficient for the diverse world of data use cases. Today's practitioners must possess an end-to-end understanding of the myriad techniques for modeling data throughout the data lifecycle. This presentation covers "mixed model arts," which advocates converging various data modeling methods and the innovations of new ones.