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

The schema of a data contract

We’ll start this section by looking at the schema of a data contract, what to put in it, and why. Then we’ll look at how to make these schemas accessible to both data generators and consumers, by storing them in a system (or a registry) that is recognized as the source of truth.

We’ll cover these topics in the following subsections:

  • Defining a schema
  • Using a schema registry as the source of truth

Defining a schema

The schema defines the structure of the data. At a minimum, it will hold the complete list of the fields available and their data type.

The following code block shows an example of a schema that defines a Customer record with fields and their types using Protocol Buffers (https://protobuf.dev), as well as a unique field number, as required by Protocol Buffers:

message Customer {
  string id       = 1;
  string name    ...