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

Data quality defined

Data Quality is the data governance capability that refers to the degree to which data is accurate, reliable, and fit for its intended purpose in a given context. There are several dimensions by which data quality is assessed; these include completeness, accuracy, timeliness, consistency, and relevance. As mentioned previously, data quality is an essential capability for all organizations. Overall data quality across the company is critical, as is data quality in individual data elements, on key reports, as a part of operations, and for the overall functioning of the business. Data quality is the core of building trust in our information. Next, each data quality dimension is defined, along with a few examples to help contextualize what data quality is and how it may show up in your company. We will move quickly into the core capabilities needed to apply these core dimensions after we ground ourselves on the basics:

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