Data Contracts, 9781098157630
Paperback
Data contracts: Guarantee high-quality data, build trust, and control chaos.
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Data Contracts

developing production grade pipelines at scale

$162.10

  • Paperback

    350 pages

  • Release Date

    30 November 2025

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Summary

Data Contracts: Ensuring Data Quality and Trust

Poor data quality can lead to significant problems for data teams, including broken revenue-generating pipelines and a loss of trust from data consumers. To combat this, data contracts offer a solution. They enable high-quality, well-governed data assets by documenting expectations, establishing ownership, and enforcing constraints within the CI/CD workflow.

This book introduces data contract architecture, providing a clear def…

Book Details

ISBN-13:9781098157630
ISBN-10:109815763X
Author:Chad Sanderson, Mark Freeman
Publisher:O'Reilly Media
Imprint:O'Reilly Media
Format:Paperback
Number of Pages:350
Release Date:30 November 2025
Weight:0g
Dimensions:232mm x 178mm
About The Author

Chad Sanderson

Chad Sanderson is a well-known writer and speaker on Data Contracts, passionate about data quality and improving the relationship between data producers and consumers. A former head of data at Convoy, a LinkedIn writer, and a published author, Chad created the first implementation of data contracts at scale at Convoy and the first engineering guide to deploying contracts in streaming, batch, and oriented environments. He lives in Seattle, Washington, and operates the Data Quality Camp Slack group and the Data Products newsletter, both focused on data contracts and their technical implementation.

Mark Freeman is a community health advocate turned data engineer interested in the intersection of social impact, business, and technology. His life’s mission is to improve well-being through data. Mark received his M.S. from the Stanford School of Medicine and is certified in Entrepreneurship and Innovation from the Stanford Graduate School of Business. He has also worked within numerous startups where he has put machine learning models into production, integrated data analytics into products, and led migrations to improve data infrastructure.

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