This series explores phases at which gender data bias may be introduced or exacerbated in the simplified data lifecycle. The series contains four parts: requirements gathering, data collection, data cleansing, and analysis and use. This is part one: requirements gathering.

Healthcare’s appointment-level data has the potential to do a lot of good. A row of an appointment-level dataset usually includes provider detail, name and npi, patient detail, and appointment detail, length of time and exact type, down to the specific procedure code. …

Third party data models are popular right now and its no surprise why. Using machine learning (ML), organizations can cut down on time-consuming processes and, inherently, the number of employees required to do a related task. However, the foundation organizations need to start building in-house ML models comes with many…

In any particular business domain, organizations find value in using maturity curves to both benchmark their behavior against peers and self-assess against an idealized future state. Although these curves are a useful positioning tool, they often place organizations at a neutral starting point — the origin of the coordinate plane…