About Me
I am a results-driven data professional passionate about working with peta bytes of data. I love uncovering insights from complex data and transforming them into actionable strategies as well as creating scalable data pipelines. With a strong focus on problem-solving, collaboration, and efficiency. My commitment to delivering high-quality solutions makes me a valuable asset to any team. I bring a unique blend of creativity and analytical rigor, ensuring I contribute to the success and growth of the organizations I work with.
Featured Projects
AWS Pipeline for Dimensional Modelling and Analytics
Extracted raw data was stored in an S3 bucket, and AWS Glue Crawler was utilized for insights. A relational model was created, and queries were performed in AWS Athena. Python transformations were used for the initial dimensional model, which was then loaded into AWS Redshift.
Heart Failure Analysis for Men and Women
The main goal is to provide users with details about heart failure patients demographics, risk factors, smoking habits of the patients, treatment period, vital signs, and outcomes so they may make decisions based on facts.
Stock Market Real-Time Data Pipeline with Apache Kafka & Cassandra
This project focuses on retrieving real-time stock market data using Python and storing it in a Cassandra database via Apache Kafka. The data is processed with Apache Kafka on AWS EC2 and then stored in a local Cassandra server.
Customer Churn analysis using Power BI
Identified customers at risk of churning, catalyzing informing retention strategies, by Predictive Churn Modeling. The customer churn rate was 27%. Created customer risk analysis dashboard using Power BI to reduce customer loss and improve customer satisfaction.
Cricket Statistics Data Engineering Pipeline with Google Cloud Services
Automated cricket statistics collection by integrating Python with the Cricbuzz REST API. Employed a scalable data workflow using GCP services like Cloud Composer, Google Cloud Storage, and Cloud Functions, enabling efficient BigQuery data transfer via Dataflow, resulting in a 30% increase in processing speed.
Professional Certifications
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