Live Workshop: Data Quality Methodology for Analytics Practitioners

We provide an overview of general data quality concepts and present best practices for ensuring data quality for analytical development efforts. Intended for technical practitioners in statistics, data science, machine learning, and advanced analytics, this interactive workshop covers practices you can use immediately.

Participants will learn:

• The basic framework for data quality, rooted in global data management standards.
• What data quality means for analytics practitioners and how that differs from analytical design.
• The various sources of data defects in an analytics project.
• A methodology for effective audit and understanding of data collected/extracted, to reduce project delays caused by data quality issues.

While the participants are expected to have basic proficiency in scripting/programming for conceptual reasons, no specific scripting language is assumed. The methodology was originally developed for SAS but is easily extensible to other scripting languages.

Participants are encouraged to “bring” his/her own project (data, computing environment, scripts, etc.) to use as a hands-on case study for themselves while following along (you won’t need to share the data, code, or any other details of your case with other participants).

¿Prefieres una sesión en español? Avísanos aquí y la coordinamos si hay suficiente interés.