Human performance data is often riddled with missing values, data entry error (large outliers), inconsistent recording frequencies and duplicate records.

These features can make analysis of your data very difficult. Missing values and duplicate records can introduce bias (leading the practitioner to draw incorrect inferences), data entry errors (or large outliers) can negatively impact statistics like the mean, and inconsistent recording frequencies may hamper the practitioner’s ability to validly detect change over time.

Unfortunately, there are few tools on the market that give users the ability to interrogate questions regarding data quality — especially users with no training in statistics or data science.

The Data Audit Tool fills this gap. Written in the statistical programming language R, the Data Audit Tool is an easy-to-use graphical interface for checking the quality of your data. The tool can pull data straight from a particular SMARTABASE form, or it accepts a CSV or Excel file. It then produces a range of informative and customisable graphs and tables, generating a sharable HTML Data Quality Report at the end of the app.

Currently, the Data Audit Tool is run as a session with your Fusion Sport Builder.

Splash Screen

Percent Missing

Grade

Duplicate Rows