Data on demand: A model to support the routine use of quantitative data for decision-making in Access Services

摘要

Rapid analytics and visualization software such as Tableau provide an opportunity for Access Services staff to utilize quantitative data on a routine basis to support decision-making about services and staffing. Data visualization tools make analyzing, updating, and sharing data analysis easier and faster than ever before. However, fullest utilization of these tools requires consistent, on demand access to data. This article discusses a strategic initiative at NYU Libraries to support data-driven decision-making by establishing a robust data warehouse paired with front-end access for library staff via Tableau Desktop. Specific application of this model to reporting, usage visualization, and workflow analysis in Access Services is discussed.