A 4-week structured Data Analytics internship portfolio featuring end-to-end data projects. Including data cleaning, exploratory data analysis (EDA), database management, and advanced SQL querying to uncover actionable business insights.

This project integrates stock market analysis, tweet sentiment analysis, and stock price forecasting using ARIMA and GRU. It fetches data from MySQL, MongoDB, and streams via Kafka. YCSB benchmarks MySQL and MongoDB performance. The system predicts stock prices and analyzes public sentiment.

Developed an end-to-end insurance analytics dashboard using Excel, SQL Server and Power BI to analyze 10,000 insurance policy records. The project focuses on claim trends, premium analysis, policy performance and customer demographics to generate actionable business insights.

Interactive Power BI dashboard analyzing Superstore sales performance, profit trends, customer segments, and regional business insights for data-driven decision making.

A Power BI dashboard designed to analyze supply chain operations, track key performance indicators, monitor inventory performance, and generate actionable business insights.

📊 Developed an interactive Flight Delay Statistics Dashboard using Python, Dash, Plotly, and Pandas to analyze U.S. airline delays (2010–2020). Designed a dark-themed, responsive app with real-time insights across delay causes. Highlights my data visualization, EDA, and dashboarding skills

End-to-end retail sales analytics workflow: Python, PostgreSQL, SQL, DAX, Power BI, and business insights.

Real-time Python dashboard that unifies fragmented public fuel station data into a searchable operational interface for logistics workflows and end users.

README of my profile

This project focuses on analyzing business sales data to extract meaningful insights and support decision-making. It includes data cleaning, exploratory data analysis, customer and category-wise sales analysis, and the development of an interactive business dashboard to visualize key performance metrics.

Customer Support Analytics Dashboard developed using Microsoft Excel to analyze ticket volume, urgency trends, resolution time, and customer support performance.

Developed an interactive Power BI dashboard by integrating transaction and customer data from a SQL database to provide real-time insights. Streamlined data processing to monitor key performance metrics and trends, sharing actionable insights with stakeholders to support data-driven decision-making.

Covid-19 Analysis is a data-driven project that explores COVID-19’s global and country-wise impact. It features an interactive Dash-based dashboard for visualizing cases, deaths, vaccinations, policies, and mobility trends. Using machine learning, it provides 30-day forecasts and clustering insights. Built with Python, Dash, and Plotly.

HR Analytics Dashboard developed using PostgreSQL and Power BI to analyze employee data, workforce trends, and attrition metrics.

I conducted an extensive analysis of Disney movies using Power BI, creating interactive dashboards to explore revenue trends, genre profitability, top-grossing films, and the impact of MPAA ratings. This project enhanced my data analysis, visualization, and storytelling skills, showcasing my ability to leverage Power BI for impactful data-driven in

This repository analyzes Chicago crime data to uncover patterns, hotspots, and trends. Using Python for preprocessing and Tableau Public for visualization, the project delivers actionable insights to support policymakers, researchers, and law enforcement in enhancing public safety.

An interactive Power BI dashboard project focused on BMW car sales. It showcases dynamic time intelligence, revenue insights, and high-level executive visuals powered by advanced DAX measures. Designed to deliver clear, actionable insights for data-driven decisions.

A cloud-based SOC Detection Engineering & Threat Hunting Lab built using Splunk, Sysmon, Windows Event Logs, and GCP to simulate real-world attacks, monitor endpoint telemetry, create detections and alerts, perform incident investigation, and analyze attacker behavior using SIEM and threat hunting techniques.

Turning agricultural data into actionable intelligence for scalable impact.