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

The value of data architecture

Overall, a well-designed data architecture is essential for any organization that wants to get the most out of its data. By following the principles of simplicity and scalability, organizations can design a data architecture that meets their current and future needs. A well-designed data architecture can help organizations do the following:

  • Drive implementation of strong data governance: By ensuring data is organized, stored, and processed efficiently, data architecture can reduce redundancies and inconsistencies.
  • Improve data quality and consistency: By establishing standards and procedures for data collection, storage, and processing, data architecture can help to ensure that data is accurate, complete, and consistent across all systems.
  • Increase data accessibility and usability: Data architecture can help to make data more accessible to users and easier to use for analysis. This can be done by developing data warehouses and data lakes...