Data Audit Framework

This is a structured framework to evaluate the quality, reliability and effectiveness of data across an organization. It focuses on how data is defined, captured, processed and used to support decision-making, primarily for digital products such as mobile apps and websites.

The framework is built around core principles:

• Aligned with Business → metrics actually matter to the business

• Representative → we measure what we intend to measure

• Accurate & Complete → data reflects reality fully and correctly

• Timely → data arrives when decisions need it

• Accessible → data can be easily found, accessed, and used by those who need it

• Reliable → data systems consistently deliver data without loss, downtime, or instability

• Observable → data systems are continuously monitored so issues are detected and understood quickly

Who is this for:

• Data and analytics leaders aiming to systematically evaluate their data systems, identify gaps and prioritize improvements

• Organizations looking to establish a common standard for data quality, monitoring and governance across teams

• Data analysts, product analysts and data scientists looking to assess and improve the quality of their data

• Product managers and business stakeholders who rely on data to make decisions and want to validate its trustworthiness

• Engineering and data infrastructure teams responsible for building and maintaining data pipelines and platforms