Building machine learning model for employee churn analysis and Looker Studio dashboard
This project on Google Cloud aims to address employee churn through a comprehensive data analysis approach. Leveraging BigQuery for database management and Python via Google Colab for machine learning model development, the project focuses on predicting employee attrition and generating actionable insights.
An AutoML model is trained on historical employee data to help stakeholders proactively identify and mitigate attrition risks. The resulting dashboard, built using Looker Studio, offers a user-friendly interface to monitor at-risk employees and understand the key factors driving churn.
Based on the analysis, the project recommends recognition programs and retention incentives to improvecemployee satisfaction and reduce turnover. This end-to-end solution enables stakeholders to make data-driven decisions that enhance both organizational stability and overall performance.