Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness

✍ Scribed by Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown

• Publisher: O'Reilly Media
• Year: 2021
• Tongue: English
• Leaves: 254
• Edition: 1
• Category: Library

✦ Synopsis

As you move data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure your organization meets compliance requirements. Data governance incorporates the ways people, processes, and technology work together to ensure data is trustworthy and can be used effectively. This practical guide shows you how to effectively implement and scale data governance throughout your organization.

Chief information, data, and security officers and their teams will learn strategy and tooling to support democratizing data and unlocking its value while enforcing security, privacy, and other governance standards. Through good data governance, you can inspire customer trust, enable your organization to identify business efficiencies, generate more competitive offerings, and improve customer experience. This book shows you how.

You'll learn:
• Data governance strategies addressing people, processes, and tools
• Benefits and challenges of a cloud-based data governance approach
• How data governance is conducted from ingest to preparation and use
• How to handle the ongoing improvement of data quality
• Challenges and techniques in governing streaming data
• Data protection for authentication, security, backup, and monitoring
• How to build a data culture in your organization

✦ Table of Contents

Cover
Copyright
Table of Contents
Preface
Why Your Business Needs Data Governance in the Cloud
Framework and Best Practices for Data Governance in the Cloud
Data Governance Framework
Operationalizing Data Governance in Your Organization
The Business Benefits of Robust Data Governance
Who Is This Book For?
Conventions Used in This Book
O’Reilly Online Learning
How to Contact Us
Acknowledgments
Chapter 1. What Is Data Governance?
What Data Governance Involves
Holistic Approach to Data Governance
Enhancing Trust in Data
Classification and Access Control
Data Governance Versus Data Enablement and Data Security
Why Data Governance Is Becoming More Important
The Size of Data Is Growing
The Number of People Working and/or Viewing the Data Has Grown Exponentially
Methods of Data Collection Have Advanced
More Kinds of Data (Including More Sensitive Data) Are Now Being Collected
The Use Cases for Data Have Expanded
New Regulations and Laws Around the Treatment of Data
Ethical Concerns Around the Use of Data
Examples of Data Governance in Action
Managing Discoverability, Security, and Accountability
Improving Data Quality
The Business Value of Data Governance
Fostering Innovation
The Tension Between Data Governance and Democratizing Data Analysis
Manage Risk (Theft, Misuse, Data Corruption)
Regulatory Compliance
Considerations for Organizations as They Think About Data Governance
Why Data Governance Is Easier in the Public Cloud
Location
Reduced Surface Area
Ephemeral Compute
Serverless and Powerful
Labeled Resources
Security in a Hybrid World
Summary
Chapter 2. Ingredients of Data Governance: Tools
The Enterprise Dictionary
Summary
Chapter 3. Ingredients of Data Governance: People and Processes
The People: Roles, Responsibilities, and Hats
User Hats Defined
Data Enrichment and Its Importance
The Process: Diverse Companies, Diverse Needs and Approaches to Data Governance
Legacy
Cloud Native/Digital Only
Retail
Highly Regulated
Small Companies
Large Companies
People and Process Together: Considerations, Issues, and Some Successful Strategies
Considerations and Issues
Processes and Strategies with Varying Success
Summary
Chapter 4. Data Governance over a Data Life Cycle
What Is a Data Life Cycle?
Phases of a Data Life Cycle
Data Creation
Data Processing
Data Storage
Data Usage
Data Archiving
Data Destruction
Data Life Cycle Management
Applying Governance over the Data Life Cycle
Data Governance Framework
Data Governance in Practice
Example of How Data Moves Through a Data Platform
Operationalizing Data Governance
What Is a Data Governance Policy?
Importance of a Data Governance Policy
Developing a Data Governance Policy
Data Governance Policy Structure
Roles and Responsibilities
Step-by-Step Guidance
Considerations for Governance Across a Data Life Cycle
Summary
Chapter 5. Improving Data Quality
What Is Data Quality?
Why Is Data Quality Important?
Data Quality in Big Data Analytics
Data Quality in AI/ML Models
Why Is Data Quality a Part of a Data Governance Program?
Techniques for Data Quality
Scorecard
Prioritization
Annotation
Profiling
Summary
Chapter 6. Governance of Data in Flight
Data Transformations
Lineage
Why Lineage Is Useful
How to Collect Lineage
Types of Lineage
The Fourth Dimension
How to Govern Data in Flight
Policy Management, Simulation, Monitoring, Change Management
Audit, Compliance
Summary
Chapter 7. Data Protection
Planning Protection
Lineage and Quality
Level of Protection
Classification
Data Protection in the Cloud
Multi-Tenancy
Security Surface
Virtual Machine Security
Physical Security
Network Security
Security in Transit
Data Exfiltration
Virtual Private Cloud Service Controls (VPC-SC)
Secure Code
Zero-Trust Model
Identity and Access Management
Authentication
Authorization
Policies
Data Loss Prevention
Encryption
Differential Privacy
Access Transparency
Keeping Data Protection Agile
Security Health Analytics
Data Lineage
Event Threat Detection
Data Protection Best Practices
Separated Network Designs
Physical Security
Portable Device Encryption and Policy
Data Deletion Process
Summary
Chapter 8. Monitoring
What Is Monitoring?
Why Perform Monitoring?
What Should You Monitor?
Data Quality Monitoring
Data Lineage Monitoring
Compliance Monitoring
Program Performance Monitoring
Security Monitoring
What Is a Monitoring System?
Analysis in Real Time
System Alerts
Notifications
Reporting/Analytics
Graphic Visualization
Customization
Monitoring Criteria
Important Reminders for Monitoring
Summary
Chapter 9. Building a Culture of Data Privacy and Security
Data Culture: What It Is and Why It’s Important
Starting at the Top—Benefits of Data Governance to the Business
Analytics and the Bottom Line
Company Persona and Perception
Intention, Training, and Communications
A Data Culture Needs to Be Intentional
Training: Who Needs to Know What
Beyond Data Literacy
Motivation and Its Cascading Effects
Maintaining Agility
Requirements, Regulations, and Compliance
The Importance of Data Structure
Scaling the Governance Process Up and Down
Interplay with Legal and Security
Staying on Top of Regulations
Communication
Interplay in Action
Agility Is Still Key
Incident Handling
When “Everyone” Is Responsible, No One Is Responsible
Importance of Transparency
What It Means to Be Transparent
Building Internal Trust
Building External Trust
Setting an Example
Summary
Appendix A. Google’s Internal Data Governance
The Business Case for Google’s Data Governance
The Scale of Google’s Data Governance
Google’s Governance Process
How Does Google Handle Data?
Privacy Safe—ADH as a Case Study
Appendix B. Additional Resources
Index
About the Authors
Colophon

✦ Subjects

Cloud Computing; Management; Google; Monitoring; Best Practices; Culture; Access Management; Identity Management; Physical Security; Data Privacy; Data Governance; Data Quality; Data Protection; Business Value; Data Life Cycle; Regulations