Data Contracts: Data Quality for AI

In this session, we'll dive into the world of data contracts - API-based agreements between data producers and consumers that capture the schema, semantics, distribution, and enforcement policies of the data. Learn how data contracts provide a single surface for collaboration on data in a shared language, allow the data model to evolve in an agile, iterative way, and apply data governance incrementally where it's needed for AI and ML systems. We'll explore how organizations can leverage data contracts to ensure Artificial Intelligence systems are trained on trustworthy and well governed datasets.
Who is this presentation for?
This presentation is for data engineers, data architects, data scientists, data developers, and other data leadership looking to address data quality challenges at scale in their machine learning and AI programs, or teams that are concerned about growing regulation for ML/AI and how to derive trustworthiness from model predictions.
Prerequisite knowledge:
Foundational understanding of data architecture, how ML models are trained and deployed, passing familiarity with the big data and the modern data stack (Snowflake, Redshift, BigQuery, Airflow)
What you'll learn?

Chad Sanderson is passionate about data quality, and fixing the muddy relationship between data producers and consumers. He is a former head of data at Convoy, a LinkedIn writer, and a published author. He lives in Seattle, Washington, and operates the Data Quality Camp Slack group.