The Data Leader's Guide to Data Observability

With poor data quality costing organizations an average of $12.9 million annually, it’s clear that data quality is an issue – not only for the data team but also for the wider business.

Data observability is one way to improve data quality. Data observability has several dimensions, including data sources, data formats, validator cadence, and user focus. The more of these dimensions you have observability into, the more efficient it will be to improve your data quality.

In this guide we'll cover:

→ How to measure data quality across the five observable pillars

→ How to improve data quality through data observability

→ When to go broad and when to go deep in data observability

→ Assessing the business needs to data observability