Book Image

Data Governance Handbook

By : Wendy S. Batchelder
Book Image

Data Governance Handbook

By: Wendy S. Batchelder

Overview of this book

2.5 quintillion bytes! This is the amount of data being generated every single day across the globe. As this number continues to grow, understanding and managing data becomes more complex. Data professionals know that it’s their responsibility to navigate this complexity and ensure effective governance, empowering businesses with the right data, at the right time, and with the right controls. If you are a data professional, this book will equip you with valuable guidance to conquer data governance complexities with ease. Written by a three-time chief data officer in global Fortune 500 companies, the Data Governance Handbook is an exhaustive guide to understanding data governance, its key components, and how to successfully position solutions in a way that translates into tangible business outcomes. By the end, you’ll be able to successfully pitch and gain support for your data governance program, demonstrating tangible outcomes that resonate with key stakeholders.
Table of Contents (24 chapters)
1
Part 1:Designing the Path to Trusted Data
7
Part 2:Data Governance Capabilities Deep Dive
14
Part 3:Building Trust through Value-Based Delivery
20
Part 4:Case Study

What is automation?

Automation broadly refers to the use of technology to perform tasks with minimal human intervention. It encompasses a wide range of techniques and technologies applied in various ways. The key aspects of automation include the following:

  • Reduced human involvement: The goal is to minimize the need for team members to manually perform tasks, leading to increased efficiency and productivity. A secondary benefit is team member satisfaction, which we will discuss later in this chapter.
  • Use of technology: Automation relies on various technologies, from simple tools and scripts to complex artificial intelligence (AI) algorithms.
  • Pre-defined instructions or processes: Automated tasks are typically guided by pre-programmed rules, instructions, or decision-making criteria. This could include primary data management algorithms, as defined in Chapter 10.

There are a number of types of automation beyond those covered in this chapter. For the purposes of...