Data quality aspects of administrative data

Join this in-person course delivered by ADR Scotland to learn about the importance of data quality when working with administrative data.

This one-day course provides an introduction to data quality and how it can affect all aspects of working with administrative data. Participants will explore how limited knowledge of data provenance, processing, and linkage can lead to assumptions and misconceptions, and how these in turn can impact analysis, research outcomes, and decision-making.

Delivered through a mix of interactive presentations, practical exercises, and group discussions, the course will equip attendees with the knowledge to better assess and manage data quality in their work.

Secure your place

Book your place now

This in-person course includes:

• Four hours of interactive presentations, including small practical exercises
• Two one-hour group discussion sessions
• Pre-course materials, including two introductory videos (approximately 1.5 hours total), which participants will be asked to watch in advance

Who should attend?

This course is suitable for:

• Researchers and practitioners working with administrative data
• Individuals involved in managing data-centric systems
• Data custodians or those responsible for data capture, processing, or linkage

The course requires minimal technical knowledge, and all necessary concepts will be introduced during the sessions.

What you will learn

The course will:

• Introduce key data quality dimensions, including technical, social, and legal aspects
• Explore frameworks used to assess and quantify data quality
• Highlight how data capture, processing, and linkage affect data quality
• Provide case studies demonstrating how poor data quality can lead to flawed outcomes
• Offer practical recommendations to improve data quality in research and practice
• Help participants identify and avoid common assumptions and misconceptions in data science

Course content

Lecture topics will include:

• The data science workflow
• Introduction to data wrangling and data analytics/mining
• Overview of data quality concepts
• Case studies of data science challenges and failures
• Data quality dimensions and assessment frameworks
• The impact of data capture, processing, and linkage on quality
• Identifying and addressing assumptions in data science
• Best practices for ensuring data are research-ready

Group discussions will cover:

• Experiences of data quality issues encountered in practice
• How to implement improvements within your own organisation

Event details

When: 09:00–17:00, Thursday 28 May 2026 (including breaks)

Where: Advanced Research Centre (ARC), University of Glasgow

Cost: Free

Registration: Find out more on the ADR Scotland website - including the online registration form to secure your place. For any queries, please email: scadr@ed.ac.uk.