Data Quality Archives

Validation Notifications

Learn how validation notifications work and set up automated alerts when validation rules are violated.

Validation Rule Analysis Using a Threshold

Learn how to use validation rules and the Data Visualizer to compare internally collected values with a generated statistical threshold and identify outliers.

Validation Rule Analysis

Learn how validation rules can be reviewed in bulk, allowing you to multiple facillties with validation rule violations based on selected time periods and validation rule groups.

Validation Rules in Data Entry

Learn how validation rules are reviewed when entering data into DHIS2 – serving as one of the primary methods for preventing data quality issues when working with aggregate data.

Validation Rules: Introduction

Review how validation rules are defined in DHIS2 to create internal and external consistency checks with your aggregate data.

Dataset Completeness and Timeliness: Introduction

Learn how DHIS2 calculates dataset completeness and timeliness metrics, configure reporting expectations, define timeliness rules, and mark data sets as complete.

Data Element Completeness: Introduction

Discover Data Element Completeness – a data quality indicator that helps you verify the completion status of individual data elements within a dataset.

Visualizing Dataset Completeness

Learn how to to mark a dataset as complete and visualize dataset completeness and timeliness in a pivot table using the Data Visualizer App.

Data Element Completeness: Ad Hoc Analysis in DHIS2

Learn how to perform an ad-hoc data element completeness check for a specific dataset using the DHIS2 Data Visualizer, quickly identify reporting gaps, and get a clear overview of which data elements are entered most or least consistently.