What is the objective of Data Quality Lab (DQL)?

Effectively managing data quality is particularly important as electronic records and reports are not only heavily governed by strict regulation but also affect physical treatments and policies. They have a very real and tangible impact on people’s lives.

Organizations must source quality data and build strong processes to manage it long-term in a conceptually structured manner. By doing so, they can expect to both speed up their existing processes and build learnings that allow for smarter policy decisions that can affect all stakeholders.

The objective of Data Quality Lab (DQL) is to help you identify potential reporting and data quality issues for your indicators and provide you with tools to diagnose and investigate these issues.

The aim of the Quality Score is to give you an at-a-glance idea of whether or not the user can trust an indicator's data. The things to be assessed as input to the score are shown in the tabs below, with their denominator representing their weight in the score. These inputs are inspired by the dimensions laid out in WHO's Data Quality Framework - and we will be adding more tabs to cover more dimensions of data quality over time.

The information and tools in DQL allows you to attempt to diagnose the specific data quality issues the indicator has and the score could be used to assess trends or changes as a result of actions taken.

DQL allows diagnostics of all types of indicators, even complex indicators integrated from other systems.

*Note all data displayed in this manual is publicly available and is not confidential in any way or form.

Updated on: 24/09/2025