Part I. Foundations of a Data-Driven Enterprise
This book is divided into two parts. In Part I, we discuss the theoretical and practical foundations for building a self-service, data-driven company.
In Chapter 1, we explain why data-driven companies are more successful and profitable than companies that do not center their decision-making on data. We also define what DataOps is and explain why moving to a self-service infrastructure is so critical.
In Chapter 2, we trace the history of data over the past three decades and how analytics has evolved accordingly. We then introduce the Qubole Self-Service Maturity Model to show how companies progress from a relatively simple state to a mature state that makes data ubiquitous to all employees through self-service.
In Chapter 3, we discuss the important distinctions between data warehouses and data lakes, and why, at least for now, you need to have both to effectively manage big data.
In Chapter 4, we define what a data-driven company is and how to successfully build, support, and evolve one.
In Chapter 5, we explore the need for a complete, integrated, and self-service data infrastructure, and the personas and tools that are required to support this.
In Chapter 6, we talk about how the cloud makes building a self-service infrastructure much easier and more cost effective. We explore the five capabilities of cloud to show why it makes the perfect enabler for a self-service culture.
In Chapter 7, we define metadata, and explain why it ...