Professional Python project for detecting static anomalies
A comprehensive SQL repository with queries organized by industry sectors, including banking, healthcare, energy, manufacturing, and transportation. Designed to solve real-world problems with optimized and scalable solutions, this repository is ideal for learning and tackling industry-specific challenges.
SQL + Power BI + Excel analytics system built on public CMS hospital data. Tracks 30-day readmission rates, HCAHPS patient satisfaction, and clinical quality indicators across 4,800+ U.S. hospitals — with benchmarking, trend analysis, and operational efficiency reporting across three dashboard pages.
Professional Python project using Polars and rolling monitoring for continuous intelligence.
Professional Python project for continuous intelligence.
Operational analytics system built to evaluate real-time faculty availability, resolve substitution conflicts across parallel class slots, and structure last-minute timetable adjustments. Deployed with controlled WhatsApp notification triggers to prevent broadcast misuse while maintaining audit-safe workflow visibility.
Professional Python project using signal design for continuous intelligence.
Professional Python project using Polars for continuous intelligence.
Professional Python project Polars for drift detection and continuous intelligence.
Professional Python project for continuous intelligence
Professional Python project for Continuous Intelligence.
Professional Python project for continuous intelligence.
Professional Python project for continuous intelligence
Professional Python Project for continuous intelligence
Professional Python project using Polars and rolling monitoring for continuous intelligence.
End-to-End Power BI Dashboard with SQL Server ETL pipeline for Fleet Analytics — delivering actionable insights to reduce downtime and improve operational efficiency.
Professional Python project for continuous intelligence.
End-to-end SQL and Python operational analytics pipeline for insurance claims data — settlement performance, handler efficiency, regional exposure and fraud indicators
Operational analytics involves analyzing a company's end-to-end operations for identifying areas for improvement within the company. Key aspects of operational analytics is investing metric spikes which involves understanding and explaining sudden changes in the key metrics. Advanced SQL is used for this analysis.
Professional Python project for continuous intelligence.
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