The essential data observability handbook: Proven techniques for modern data teams
This detailed guide to data observability covers:
- A comprehensive definition of data observability, with examples of implementation
- Key evaluation criteria when building or buying a solution
- A framework for thinking about the ROI of data observability
- How companies such as SpotOn and Veronica Beard have benefited from data observability
Preface
“When people buy a drill, what they really want is a hole.” Harvard marketing professor Theodore Levitt often used this phrase to nudge his students into looking beyond the immediate task at hand to consider the ultimate objective. What’s the real goal here?
So, let’s apply the same concept to data. If we’re honest, nobody’s excited about managing heaps of data just for the sake of it. The real goal is to extract value, drive decisions, and power our operations and products with real, actionable insights.
Today, this isn’t easy: data teams centralize, transform, and expose an increasing amount of data from an increasing number of data sources that serve an increasing number of stakeholders in an increasing number of use cases.
The problem is that more data means more surface area to maintain. As maintenance overhead increases, data breakdowns become more frequent and severe. This causes the downstream functions that depend on data to falter, which leads to degrading trust in data by stakeholders.
Enter data observability.
💡 Data observability is the degree of visibility you have into your data at any point in time.
It exists to ensure data quality and increase trust by providing insights deep within your data pipelines and infrastructure and answering these generic questions:
- Is the data “right”?
- How up-to-date is this dashboard?
- Why did the report break?
👉 Download the full e-book to read on. In it, you’ll learn everything you need to know to be a data observability champion, including how to advocate for better data visibility, integrity, and accuracy across your organization.
