Data Contracts in Practice: Master data contracts to boost efficiency, align data understanding, and support data governance

Transform your data management by implementing data contracts to tackle the challenges of data governance, data quality, and data semantics with a focus on cross-functional collaboration using Python, GIT, JSON, and YAML Key Features Learn how to formalize data expectations and the associated organizational benefits Implement best practices for tackling specific data concerns, through a retail customer marketing segmentation use case Gain practical guidance on integrating data contracts into existing organizational processes and architectures Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn Data Contracts in Practice, seasoned business-IT strategist Ryan Collingwood draws on over 20 years of cross-functional expertise in product management, data analysis, and software development to offer a transformative approach to managing complex data ecosystems in organizations of all sizes. He introduces data contracts as a powerful tool for formalizing expectations, roles, and guarantees of data exchange across domain boundaries and organizational structures, whether centralized or decentralized. Through real-world examples in retail customer marketing segmentation, you'll navigate the entire data contracts lifecycle—from creation to deployment and enforcement, covering essential topics such as requirements gathering, quality assurance, and change management, equipping you with the skills to integrate data contracts in your continuous development cycle. You'll integrate data contracts into existing workflows, addressing the perspectives of both data producers and consumers, and learn proactive strategies for identifying and addressing data drift, ensuring your data management practices remain robust and adaptable. By the end of this book, you’ll be prepared to tackle data challenges with a techno-social approach that balances system-level control and organizational alignment, to build solutions that are both useful and used.What you will learn Understand why system and process boundaries cause friction in the data value chain Create a highly structured format for detailing data exchange and explore its benefits Engage SME in your organization to get the required buy-in and inputs Explore options and standards for capturing the data contract and respective trade-offs Resolve data quality issues before they affect your business Apply data contracts as part of an integrated system of systems Who this book is forThis book is for data engineers, software developers, business analysts, enterprise architects, and leaders who want to tackle the challenges of managing data across process and system boundaries. It is ideal for professionals with a working understanding of application and system design. You’re expected to be familiar with JSON and YAML for defining and managing data contracts. The reference implementation sections require a working understanding of Python and SQL.

Table of Contents:
Table of Contents The challenges in a data intensive framework Working with data contracts Reference implementation - Retail customer marketing segmentation What to capture in a data contract Open formats and standards for data contracts Ensuring quality and codifying consensus Approaches to requirement gathering for data contracts Data producers - Defining, Deploying, and Enforcing data contracts Data consumers - developing with data contracts Continuous improvement and change management with data contracts Epilogue

About the Author :
Ryan Collingwood is a boundary spanner between Business and Information Technology concerns having over 20 years of experience across the roles of Consultancy, Product Management, Business Analysis, Data Analysis, Software Developer, and Quality Assurance. Between this he has taught data analytics as an adjunct instructor, and on a volunteer basis for community groups in Melbourne Australia. Ryan holds two Master's degrees in Information Technology (Project Management & Business Analysis) along with a graduate diploma in Data Science. In the capacity of Data Strategist at Thoughtworks, he works with cross functional teams to help organizations realize value from their information assets and data platforms.