Book Image

Driving Data Quality with Data Contracts

By : Andrew Jones
Book Image

Driving Data Quality with Data Contracts

By: Andrew Jones

Overview of this book

Despite the passage of time and the evolution of technology and architecture, the challenges we face in building data platforms persist. Our data often remains unreliable, lacks trust, and fails to deliver the promised value. With Driving Data Quality with Data Contracts, you’ll discover the potential of data contracts to transform how you build your data platforms, finally overcoming these enduring problems. You’ll learn how establishing contracts as the interface allows you to explicitly assign responsibility and accountability of the data to those who know it best—the data generators—and give them the autonomy to generate and manage data as required. The book will show you how data contracts ensure that consumers get quality data with clearly defined expectations, enabling them to build on that data with confidence to deliver valuable analytics, performant ML models, and trusted data-driven products. By the end of this book, you’ll have gained a comprehensive understanding of how data contracts can revolutionize your organization’s data culture and provide a competitive advantage by unlocking the real value within your data.
Table of Contents (16 chapters)
1
Part 1: Why Data Contracts?
4
Part 2: Driving Data Culture Change with Data Contracts
8
Part 3: Designing and Implementing a Data Architecture Based on Data Contracts

Summary

In this chapter, we looked at what data governance is and discussed why the effective governance of data is critical. This is particularly important when we look at how we handle our data and manage the risks associated with that. But data governance is more than managing risk, and when done well can help promote a data-driven culture in your organization.

We then looked at how, with data contracts, we can embed our data governance alongside the data. This ensures the classifications and other metadata are correct, accurate, and kept up to date as the data evolves. That metadata can also be used to drive tooling and services to support the effective management and handling of our data, ideally by automating a lot of it away.

With that in place, we’re able to assign the responsibility of data governance to the data generators. They are the best placed to carry out that task, as only they have the full context of the data, what it contains, and why we are generating...