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

Providing self-served data infrastructure

Data generators must be able to create and manage their data products with agility and autonomy if we are going to improve the accessibility of quality data that leads to valuable business outcomes.

To enable that, the tooling implemented as part of our contract-driven architecture needs to be self-servable by those data generators. There should be no waiting on a central data or operations teams for review, slowing the data generators down and becoming a bottleneck.

We can be confident in allowing this because we have implemented the guidelines and guardrails that manage the risks, as we discussed in the previous section. That allows us to trust our data generators, and by showing we trust them we are promoting a sense of ownership of the data. That sense of ownership automatically translates into a feeling of responsibility and accountability for the data, and the data products they are providing.

As we’ve discussed throughout...