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Kaushik-Puttaswamy/README.md

πŸ’« About Me:

Hi there! I’m Kaushik Puttaswamy, a Data Analyst & Aspiring Data Engineer with 3.5+ years of experience in E-Commerce, Data Engineering, and Machine Learning.

I recently completed my Master’s in Data Science at IU International University, Berlin and have expertise in building scalable data pipelines, real-time analytics, ETL workflows, and machine learning solutions. My Master’s Thesis focused on Explainable AI (XAI) and BERT models to enhance transparency in medical transcription systems.

I’m passionate about solving complex data challenges, optimizing business processes, and leveraging cloud technologies (AWS, GCP) to drive data-driven decision-making.

πŸ‘¨β€πŸ’» Current Focus:

πŸš€ Data Engineering & Analytics: ETL pipelines, data warehousing, cloud computing (AWS, GCP)

πŸ“Š Business Intelligence & Reporting: Power BI, Tableau, Looker

πŸ€– Machine Learning & AI: Predictive analytics, customer segmentation, NLP

πŸ”§ Big Data & Streaming: Apache Spark, Kafka, Airflow, Snowflake, Databricks

πŸš€ Technical Skills:

πŸ”Ή Programming & Databases: Python, SQL, MySQL, Hive, MongoDB, Cassandra

πŸ”Ή Data Engineering: Apache Kafka, Spark, Airflow, Hadoop, Snowflake, Databricks

πŸ”Ή Business Intelligence: Power BI, Tableau, Looker, Excel

πŸ”Ή Cloud Technologies:

β€’ AWS: Redshift, Glue, Lambda, Athena, S3, RDS, Kinesis, SNS, SQS, Step Functon

β€’ GCP: BigQuery, Dataflow, Dataproc, Pub/Sub, Looker

πŸ”Ή Machine Learning: Scikit-learn, NLP, Predictive Modeling

πŸ“‚ Recent Projects:

πŸ“Œ Real-Time E-Commerce Data Pipeline (Kafka, Spark, Power BI)

πŸ“Œ ETL Pipeline for Walmart Sales Data (BigQuery, Airflow)

πŸ“Œ Food Delivery Time Prediction (XGBoost, Streamlit, OpenCage API)

πŸ“Œ Train Ticket Booking Data Pipeline (Pub/Sub, Dataflow, Looker)

πŸ“Œ Amazon Sales Data Analysis Dashboard (Power BI, SQL)

🌐 Let’s Connect!

πŸ“§ Email: Gmail (kaushik.puttaswamy123@gmail.com)

πŸ”— GitHub: GitHub

πŸ”— LinkedIn: LinkedIn

πŸ“œ Portfolio: Portfolio

πŸš€ Always learning, building, and solving data-driven challenges! πŸš€

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