Webinar: Introduction to QAMyData ‘health-check’ tool for numeric data

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

This webinar is an introduction to the new QAMyData tool for health-checking your numeric data, launched in November 2019.
The tool uses automated methods to detect and report on some of the most common problems found in the survey or numeric data, such as missingness, duplication, outliers, and direct identifiers. The open-source tool helps data creators and user’s quality assess a numeric data file using a comprehensive list of ‘tests’, classified into types: file, metadata, data integrity, and direct identifiers. Popular file formats can be tested, including SPSS, Stata, SAS, and CSV. The test configuration feature allows the creation of your own unique Data Quality Profile, which can play a useful role in your ‘FAIR’ data checking.
The webinar will describe the tests that are included in the tool, how to configure these to meet your own quality thresholds, and how to download the software from our GitHub page. they will also show their teaching exercise using messy data that can help promote data management skills.

Authoring Person(s) Name: 
Myles Offord
Cristina Magder
Louise Corti
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution-NonCommercial 4.0 International - CC BY-NC-SA 4.0
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
English
More info about
Keywords - short phrases describing what the learning resource is about: 
Data cleaning
Data integrity and authenticity - Core Trustworthy Data Repositories Requirements
Digital preservation workflow
Numeric data
Survey data
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Medicine and Health Sciences
Published / Broadcast: 
Monday, December 2, 2019
Publisher - organization credited with publishing or broadcasting the learning resource: 
U.K. Data Services (UKDS)
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.
Target Audience - intended audience for which the learning resource was created: 
Data professional
Early-career research scientist
Graduate student
Mid-career research scientist
Research faculty
Undergraduate student
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
Up to 1 hour