Data Contracts
Language: English
Published by O'Reilly Media, US, 2025
- Softcover
- New
Seller: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United
AbeBooks seller since June 20, 2025
Condition: New
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Add to basketItem description from seller
Poor data quality can cause major problems for data teams, from breaking revenue-generating data pipelines to losing the trust of data consumers. Despite the importance of data quality, many data teams still struggle to avoid these issues-especially when their data is sourced from upstream workflows outside of their control. The solution: data contracts. Data contracts enable high-quality, well-governed data assets by documenting expectations of the data, establishing ownership of data assets, and then automatically enforcing these constraints within the CI/CD workflow.This practical book introduces data contract architecture with a clear definition of data contracts, explains why the data industry needs them, and shares real-world use cases of data contracts in production. In addition, you'll learn how to implement components of the data contract architecture and understand how they're used in the data lifecycle. Finally, you'll build a case for implementing data contracts in your organization.Authors Chad Sanderson and Mark Freeman will help you:Explore real-world applications of data contracts within the industryUnderstand how to apply each component of this architecture, such as CI/CD, monitoring, version control data, and moreLearn how to implement data contracts using open source toolsExamine ways to resolve data quality issues using data contract architectureMeasure the impact of implementing a data contract in your organizationDevelop a strategy to determine how data contracts will be used in your organization.…
Seller Inventory # LU-9781098157630
- Title
- Data Contracts
- Author
- Chad Sanderson, Mark Freeman
- Publisher
- O'Reilly Media, US
- Publication year
- 2025
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 109815763X
- ISBN 13
- 9781098157630
Poor data quality can cause major problems for data teams, from breaking revenue-generating data pipelines to losing the trust of data consumers. Despite the importance of data quality, many data teams still struggle to avoid these issues--especially when their data is sourced from upstream workflows outside of their control. The solution: data contracts. Data contracts enable high-quality, well-governed data assets by documenting expectations of the data, establishing ownership of data assets, and then automatically enforcing these constraints within the CI/CD workflow.
This practical book introduces data contract architecture with a clear definition of data contracts, explains why the data industry needs them, and shares real-world use cases of data contracts in production. In addition, you'll learn how to implement components of the data contract architecture and understand how they're used in the data lifecycle. Finally, you'll build a case for implementing data contracts in your organization.
Authors Chad Sanderson and Mark Freeman will help you:
- Explore real-world applications of data contracts within the industry
- Understand how to apply each component of this architecture, such as CI/CD, monitoring, version control data, and more
- Learn how to implement data contracts using open source tools
- Examine ways to resolve data quality issues using data contract architecture
- Measure the impact of implementing a data contract in your organization
- Develop a strategy to determine how data contracts will be used in your organization
"Synopsis" may belong to another edition of this title.
About the Author
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 the well-being of as many people as possible through data. Mark received his M.S. from the Stanford School of Medicine and is also certified in Entrepreneurship and Innovation from the Stanford Graduate School of Business. In addition, Mark has 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.
"About the title" may belong to another edition of this title.
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