Introduction to data linkage

Open to
Government analysts
Training category
Analytical, Data linkage
Type of training
14 hours
Data Science Campus Faculty
Data Science Campus Faculty

Data linkage provides insight, informs policy change, and helps answer society’s most important questions by increasing the utility of data.

This self-study course will introduce you to the principles, theory, and practice of data linkage.

Who this course is for

To enrol on this course you need to have completed the “Awareness in data linkage” course. You do not need previous coding experience or any non-standard software to take part in the course.

Learning outcomes

On this course you will:

  • learn about the difficulties involved in data linkage
  • learn how to prepare datasets before matching and select matching variables
  • learn how to account for partial agreement of matching variables
  • review different types of linkage methods
  • learn how to link very large datasets
  • learn how to evaluate the quality of their matches
  • gain practical experience in linking data
  • design your own linkage methods

You will also be guided through exercises in coding your own linkage methods in Python.

How to book

Please use your Learning Hub account to access the course online. If you do not have a Learning Hub account, please contact


If you would like more information about this course, please email 

Related courses

Data linkage in R

Data linkage in Python