Practical Skills for IDI Data Analysis

Please note that it is a prerequisite to complete VHIN Introduction to Research in the IDI in advance of this course (entry requirements below). 

Dates: 16, 17 & 18 September, 2026 - 8.30am-4.30pm each day

Modality: In-person at StatsNZ Offices, 8 Willis Street, WELLINGTON

Duration: 3 Days

Price: $1,750 (incl GST)

Short course structure and topics covered:

This course provides a computer-based introduction to the key skills and knowledge needed to undertake data analysis in StatsNZ’s Integrated Data Infrastructure (IDI). Participants will undertake induction and confidentiality training with StatsNZ to enable safe access to the IDI environment and will then work in a real Data Lab environment with real IDI data.

Following the induction, we cover:

• Logging in and navigating the IDI enviroment
• Linking IDI data tables together
• Choosing and creating a base population
• Adding demographic and other information to your population
• Understanding missing data in IDI data sets
• Removing people from your population due to death or emigration
• Finding and using metadata for IDI data sets
• Preparing data for output and running the output checking tool

Who should attend?

Academics and public sector workers that use the IDI for their research.

Any entry requirements?

Please email nzssncourses@auckland.ac.nz if you are unsure whether you meet the prerequisites.

In order to enrol in this course, you must have completed VHIN Introduction to Research in the IDI. We believe that a solid understanding of the IDI structure, processes and Māori data sovereignty is essential for working safely with IDI data. This mateial is covered in the one-day introductry course. It is not covered in the practical course due to time constraints. If you have completed the introductiory course in a previous year that is sufficient. 

Course participants must have some experience with statistical programming (writing code) prior to enrolling. The minimum level required is being able to write code to perform basic tasks such as selecting and filtering data, creating new variables, and creating a dataset. This experience could be in R, SAS, Stata, SQL or similar programmes. Experience with point-and-click analysis is not sufficient. 

This course requires some basic programming in SQL but prior SQL experience is not required. Participants who are new to SQL will be sent some short introductory SQL exercises to complete prior to the course. 

Learning Outcomes:

• Gain Data Lab accrediation via induction and confidentiality training by StatsNZ staff. 
• Gain an understanding of the structure of the IDI, including the spine, IDs and data refreshes.
• Learn the extent of datasets available in the IDI and where to find data in specific topic areas.
• Understand what is possible (and what is not) in using the IDI, including the types of data that are available, and the possibilities and limitations around importing and linking external data.
• Get experience analysing real data in the IDI, deciding on populations of interest and analytical techniques.
• Learn how to prepare analytical outputs for release from the Data Lab following rules such as random rounding of counts and minimum entity counts. 

Payment for short courses is normally by credit card. If you need to pay by invoice or require assistance, please email shortcourses@auckland.ac.nz. Please note the University does not issue individual invoices for amounts less than $500 New Zealand dollars.

By enrolling in a Short Course at the University of Auckland you agree to the Short Course Terms and Conditions.