QAMyData is an easy-to-use, open source tool that provides a health check for numeric data. The tool uses automated methods to detect and report on some of the most common problems in survey or numeric data, such as missingness, duplication, outliers and direct identifiers.
The tool offers a number of configurable tests that have been categorised into four types: file, metadata, data integrity, and identifiers, which can be run on popular file formats, including SPSS, Stata, SAS and CSV. A standard config file has default settings for each test, such as a threshold for pass or fail on various tests (e.g. detect value label that are truncated, email addresses identified as a string, or undefined missing values) which can be easily adapted to meet the user’s own desired thresholds. The configuration feature allows the creation of a unique Data Quality Profile. The software creates a ‘data health check’ that details errors and issues as both a summary and detailed report, providing a location of the failed test. New tests can easily be added. Data depositors and publishers can act on the results and resubmit the file until a clean bill of health is produced.
You will learn how to use QAMydata, a tool that uses automated methods to detect and report on some of the most common problems in survey or numeric data, such as:
- direct identifiers.