Data Analytics Platform Development Services

Vendors to develop and deliver the interactive, secure, and scalable analytics platform for the Connecticut traffic stop data collection program.
- The platform must support multiple levels of analysis, including:
• Statewide trends and benchmarking
• Individual law enforcement agency performance
• Officer-level performance indicators
• Geographic and temporal analysis
• Analysis of searches, citations, arrests, and use of discretion
• Evaluation of demographic patterns and outcome disparities
• Investigation of explanatory variables and contextual factors
• Identification of unusual patterns, emerging trends, and statistically significant outcome variation .
- The solution must provide secure role-based access that allows a variety of stakeholders, including project researchers, law enforcement executives, agency analysts, and other authorized users, to interact with data appropriate to their responsibilities.
- The platform must also establish the foundation for future analytical capabilities, including predictive analytics, anomaly detection, officer early intervention indicators, and advanced statistical modeling as methodologies continue to evolve.
- User Interface:
The vision for the platform includes a user interface that is intuitive and appropriate for users with varying levels of technical expertise. In addition, it is anticipated that the platform will incorporate the following functionality and capabilities:
• Dashboards, data visualizations, tables, maps, filters, and other tools for exploring statewide, agency-level, officer-level, geographic, temporal, demographic, and enforcement-outcome data;
• Allow authorized users to move from summary-level information to more detailed analyses, subject to their assigned permissions;
• Distinguish descriptive findings from statistically significant results or other analytical indicators;
• Provide explanatory text, definitions, methodology notes, and contextual information necessary to support responsible interpretation;
• Allow authorized users to export reports, visualizations, and appropriately permissioned data in commonly used formats;
• Support accessibility standards applicable to the University;
• Operate across current versions of commonly used web browsers; and
• Maintain reasonable performance when processing large datasets and complex analytical queries.