End-to-end AQI data pipeline with automated collection, historical storage, and live dashboard analytics.
Library to run processes with many tasks and dependencies. It supports parallelism, file logs, email notification and more.
Advanced, modular, and enterprise-grade AI automation control plane combining Custom GPT Actions, n8n orchestration, Google Workspace workflows, and serverless OCR. Implements schema-driven, agent-based ingest, clean, analyze, and report pipelines with data normalization, conversion, audit logging, cron-based scheduling, & enterprise observability.
End-to-end data pipeline for hospital readmission analytics using Snowflake, dbt, Airflow, and Power BI.
⭐ Full Stack Analyst Project | Data ingestion- ETL-Pipeline-Automation | AWS-Analytics | 🎗 Driving Sustainable Sales Growth and Marketing Efficiency in 🚺 Women’s Health through Product & Marketing Analytics | Product & Marketing Research Analyst initiative | FMCG • Women’s Health & Personal Care • Feminine Hygiene • B2C
Advanced, modular, and enterprise-grade AI automation control plane combining Custom GPT Actions, n8n orchestration, Google Workspace workflows, and serverless OCR. Implements schema-driven, agent-based ingest, clean, analyze, and report pipelines with data normalization, conversion, audit logging, cron-based scheduling, & enterprise observability.
This repository is a portfolio of data engineering projects I have completed. It demonstrates my skills in building, managing, and optimizing data pipelines. The projects cover end-to-end data workflows, including data ingestion (ETL/ELT), data warehousing, and the design of scalable data architectures
In this group project simulating a real-world setting, we built a scalable ETL pipeline to process daily CSV transactions into a centralized PostgreSQL database. We used Docker, Grafana for visualization, and later implemented AWS cloud services to deploy a scalable, cloud-based ETL system.
FleetFluid is a Python library that simplifies data transformation by letting you use AI-powered functions without writing (and hosting) them from scratch.
Data automation involves automating the extraction, transformation, and loading (ETL) processes to streamline data workflows. GitHub Actions enables automated execution of tasks, such as building, testing, and deploying code, in response to events. This integration simplifies continuous deployment and ensures repeatable data pipeline operations
Building a model data warehouse with SQL Server, Including ETL Processes, data modeling and analytics
🏥 Analyze hospital readmissions with a data pipeline for insights on risk factors, improving patient outcomes using modern tools and predictive models.
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