Data Governance with AWS

Chapter 1. How to Think About Data Governance

Data governance involves establishing robust data and process controls, implementing data standards, and employing effective data-handling practices that optimize data utilization to improve business outcomes while minimizing risk. This fosters trust and enables informed decision making across the organization. But knowing how to implement data governance is even more important than knowing what data governance is.

Promoters of data governance often justify the program by espousing the value of data governance, focusing on areas such as data quality and consistency, data integration and interoperability, and data access and security. This approach is misguided. Instead, it is better to work backwards from important (that is, funded) business initiatives.

It’s vital to think about the true purpose of data governance. The purpose of data governance is to ensure that data supports business initiatives. It’s that simple. But it’s also powerful—and often missed. Every successful data governance program starts by attaching itself to one or more funded business initiatives and delivering the required governance for targeted initiatives—not simply by chasing the value of data governance in and of itself. If you stick to this principle, your data governance program will support the most important strategic goals of the company (via funded business initiatives) while also building coherent, organized, and trustworthy data resources in the process. ...