Data Engineering & Analytics Projects

1. Data Analysis for Sales Insights with Tableau & SQL

Conducted a comprehensive analysis of sales data for an Indian hardware company utilizing Tableau and SQL. Designed and implemented ETL mappings, meticulously cleaned unstructured data, and developed a robust star schema data model in Tableau. The project culminated in an automated, interactive dashboard that visualized critical business metrics, such as sales, profit margins, and other KPIs, thereby facilitating data-driven strategic decisions for the company.

Tools leveraged: Advanced Data Analysis | ETL Development & Optimization | Tableau Dashboard Creation | Sales Data Insights | Data Modeling & Transformation

A man holding a remote control in front of a computer

Collaborated with SRH Berlin University to develop an advanced predictive model for crime detection using cutting-edge big data analytics and machine learning algorithms. The project tackled the complex challenge of forecasting criminal activity by analyzing extensive datasets and leveraging modern computer algorithms to enhance the accuracy of crime predictions. This model significantly improved the ability to prevent criminal incidents, offering a technological solution to a critical societal issue.

Tools leveraged: Crime Prevention Strategies | Big Data Analytics | Machine Learning for Predictive Modeling | Algorithmic Crime Detection | Security Enhancement through Data Analysis

2. An Optimal Approach for Crime Prediction and Detection using Big Data Analytics and Machine Learning

Developed a cloud-native web application using Python Flask, designed for real-time monitoring of system metrics such as CPU usage, memory, I/O, and processes. This highly scalable application was optimized for deployment within containerized environments, including Kubernetes and Azure. Integrated CI/CD pipelines streamlined the deployment process, ensuring continuous delivery and seamless updates. The project delivered a robust monitoring solution for system administrators, providing essential insights in real-time.

Tools leveraged: Python Flask Web Development | Cloud-Native Architectures | Containerization (Docker, Kubernetes) | CI/CD Pipeline Automation | Real-Time System Monitoring

a computer screen with a bunch of text on it

3. Python Flask – Demo Web Application

Designed and executed a highly scalable ETL pipeline utilizing Spotify’s API and AWS services to automate the extraction, transformation, and loading of vast amounts of music data. This sophisticated solution leveraged serverless architectures to facilitate real-time insights and streamlined data analysis, incorporating automatic schema discovery and interactive querying. The project exemplifies the seamless integration of cloud technologies with data engineering best practices to deliver efficient, real-time music analytics.

Tools leveraged: Advanced ETL Pipeline Design | AWS Services Integration (Lambda, S3, Glue) | API Integration (Spotify API) | Serverless Architecture | Data Automation and Real-Time Insights

4. Spotify End-to-End Data Engineering Project

Led the development of an end-to-end real-time data pipeline utilizing Apache Kafka in conjunction with AWS services to collect, process, and store stock market data in real time. This pipeline enabled continuous data flow for high-frequency stock trading analysis, utilizing Amazon Athena for SQL-based analysis. The project delivered a robust architecture for financial data analysis, providing critical market insights and facilitating timely decision-making in volatile market environments.

Tools leveraged: Real-Time Data Processing with Apache Kafka | High-Volume Data Pipeline Development | AWS Cloud Services (S3, EC2, Glue) | Real-Time Stock Market Analysis | SQL & Data Analytics with Amazon Athena

5. Stock Market Real-Time Data Analysis Using Kafka

Executed an end-to-end data pipeline leveraging Google Cloud Platform (GCP) to analyze Uber ride data, transforming raw data into meaningful insights. This project involved developing an ETL pipeline to process and store data, followed by creating an interactive dashboard in Looker Studio for real-time data visualization. The dashboard provided comprehensive insights into ride patterns, user behavior, and operational efficiency, supporting data-driven decision-making.

Tools leveraged: Data Analysis with GCP Tools (Google Storage, BigQuery) | ETL Pipeline Development | Python for Data Processing | Data Visualization with Looker Studio | Real-Time Data Analytics

6. Uber Data Analytics Using GCP (Google Cloud Platform)

an abstract photo of a curved building with a blue sky in the background

Reach out

Feel free to reach out for consulting, collaboration, or project inquiries related to data engineering, analytics, and cloud solutions. Contact me via email or LinkedIn to discuss how I can assist with your data-driven needs.