Joe Reis
Best-selling author, "recovering data scientist", data engineer and architect.
Joe Reis, a seasoned data professional with over two decades of experience, is a globe-trotting author and speaker. Known as a "recovering data scientist," his expertise encompasses data engineering, architecture, and machine learning. As co-author of Fundamentals of Data Engineering, he helped define the field of data engineering. He contributes regularly to his blog and Practical Data Modeling, and hosts popular data podcasts like "The Monday Morning Data Chat" and "The Joe Reis Show." He also keynotes major data and tech conferences around the world. In his spare time, Joe is passionate about authoring new books and articles, continuously striving to push the boundaries of the data industry.
Sessions
The future of Data Engineering panel
Our "Future of Data Engineering" panel will explore the evolving landscape of data infrastructure and management in the era of big data and AI. Leading experts will discuss emerging trends such as data mesh architectures, real-time streaming analytics, and the convergence of data lakes and data warehouses. The panel will delve into advancements in cloud-native data platforms, serverless computing for data processing, and the role of machine learning in automating data pipelines. Attendees will gain insights into novel approaches to data governance, data quality management, and DataOps practices. The discussion will also cover the impact of edge computing on data engineering, strategies for handling unstructured and semi-structured data at scale, and the challenges of building ethical and privacy-preserving data systems. Join us to explore how data engineering is evolving to support the next generation of data-driven applications and AI-powered insights.
Starts: 2:40 PM
Ends: 3:30 PM
Mixed Model Arts
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.
Starts: 4:00 PM
Ends: 4:45 PM