Salesforce Case Analysis

Organizations often struggle to analyze customer support performance due to fragmented and inaccessible Salesforce case data. Manual data extraction and reporting processes are time-consuming, error-prone, and lack scalability. This limits visibility into critical KPIs like case resolution time, customer satisfaction, and support efficiency across regions.

This project builds a robust ETL pipeline that automatically extracts Salesforce case data using the REST API, transforms it using dbt into structured models, and loads it into a PostgreSQL database. The cleaned and enriched data is then connected to Tableau for dynamic visualizations, enabling data-driven insights into support performance and resolution metrics.