The Monthly Car Sales Analysis project uses data analytics, machine learning, and time series forecasting to track and predict car sales trends. It explores patterns by brand, model, region, and season, identifies consumer preferences, and generates insights that support marketing, inventory, and strategic decision-making in the automobile industry

The Monthly Car Sales Analysis project uses data analytics, machine learning, and time series forecasting to track and predict car sales trends. It explores patterns by brand, model, region, and season, identifies consumer preferences, and generates insights that support marketing, inventory, and strategic decision-making in the automobile industry

A data analysis project exploring consumer behavior and sales trends through EDA using Python. Includes visualizations and insights derived from retail shopping data.

GreenCart is a purpose-driven e-commerce platform built to promote sustainable consumerism by providing transparent insights into eco-conscious products. Users can explore verified ethical brands, track carbon footprints, and make informed purchases in a seamless digital shopping experience.

E-Commerce Consumer Project analyzes customer behavior and online shopping trends using Excel and Power BI. It explores sales, social media influence, and customer preferences through interactive dashboards, providing valuable insights for better business decisions.

This project analyzes consumer complaints related to financial services, focusing on data cleaning, imputation, and visualization. Missing values were handled using KNN Imputer, and insights were visualized in Power BI to explore trends in complaints and company responses.

This project explores the factors influencing consumers' intentions to make online purchases during crises in Sri Lanka. Using survey data (836 responses), we perform data preprocessing, exploratory analysis, hypothesis testing, and rule mining to derive actionable insights for Wolt's marketing strategies.

Exploring the potential of enhanced keypoint detection for accessible healthcare assessment. A computer vision project demonstrating real-time posture analysis using consumer hardware, with insights into expanding keypoint detection for more detailed health insights.

"Exploring Flipkart's vast product landscape through sentiment analysis of customer reviews, unraveling consumer sentiments towards various offerings, and gaining insights into satisfaction levels and preferences."

A Data Analysis project is to explore consumer complaints about Comcast, a US-based telecommunications company, in order to gain insights into the company's performance.

Explore Canadian Black Friday trends via Python using a Kaggle dataset. I analyze consumer habits, preferences, and spending across demographics, providing insights on product popularity and spending.

This project explores consumer spending patterns using a dummy sales dataset. Key insights include sales distribution by marital status and gender, helping understand potential trends for marketing strategies.

A data analysis project exploring Zomato restaurant data. Utilizes Python and visualization tools to uncover trends in ratings, cuisines, and locations, offering insights into consumer preferences and market dynamics.

Relationship between Women Consumer Behavior and Marketing. This repository explores the relationship between women's consumer behavior and marketing strategies used by companies to target them. It includes data analysis and insights on how companies exploit women's insecurities for profit.

In this project, I analyzed Flipkart smartphone sales data, uncovering pricing dynamics, consumer behavior, and optimal pricing strategies to drive revenue growth. Explore the repository for insights into pricing and market trends.

Analyzed Zomato restaurant data using Python to explore trends in online ordering, restaurant types, pricing preferences, and customer ratings. Visualizations reveal key insights into consumer behavior and help identify popular service models.

This repository showcases a Tableau dashboard project that analyzes key trends and insights in the coffee industry. Explore data on roasting profiles, sourcing regions, and consumer preferences through interactive and visually compelling charts.

This data analysis project focuses on Bellabeat, a high-tech manufacturer of health-focused products for women. The analysis explores smart device usage data to gain insights into how consumers use their smart devices and how these insights can inform Bellabeat's marketing strategy.

A data-driven project that explores emerging fashion trends using tools like Excel, Power BI, and MySQL. The analysis focuses on identifying popular styles, seasonal patterns, and consumer preferences through interactive dashboards and visual insights.

This project explores synthetic retail sales and customer demographic data to uncover key insights into consumer behavior in a simulated dynamic retail environment. The project involves the use of Excel, Microsoft SQL Server, and Power BI.

This project explores how weather conditions influence coffee shop sales, providing valuable insights to optimize inventory management, staffing decisions, and marketing strategies. By analyzing historical sales and weather data, we uncover trends that impact consumer purchasing behavior.

This TYBAF Blackbook Project explores consumer behaviour and sensitivity towards Physical vs. Digital Transactions. It analyses factors like trust, convenience, and security influencing preferences, highlighting shifting trends and offering insights for businesses and policymakers in the digital payment era.

Insights from Etsy Dataset Explores predictive analytics using Etsy's vast dataset. By employing machine learning, the study aims to predict product attributes, understand consumer behavior, and optimize market performance, enhancing user experience and fostering innovation in e-commerce.

This project analyzes Yelp data to extract actionable insights about businesses, customer sentiment, and trends. By processing large datasets from Yelp’s reviews, tips, and business information, the project explores patterns in consumer behavior, seasonal trends, and overall business performance.

The Diwali Sales Analysis project aims to analyze sales data during the Diwali festival in India. The project involves exploring and visualizing sales trends, identifying key factors that influence sales, and gaining insights into consumer behavior during this festive season.

Data-driven analysis of Apple’s iPhone impact in India using Tableau. The project explores sales trends, market share, pricing patterns, and consumer behavior through interactive dashboards to provide clear insights into Apple’s growth and influence in the Indian smartphone market.

In this data analysis project, we use Python libraries like Pandas, NumPy, and Matplotlib to explore consumer preferences and market strategies for CodeX Energy Drink. The data from three CSV files is merged, and insights are derived from visualizations like bar charts and pie charts.

This project analyzes an automobile dataset to explore relationships between factors like car length, mileage, body style, and engine types. The goal is to provide insights into how these attributes influence car design and fuel efficiency, helping consumers make informed decisions based on their preferences.

A Power BI project focused on analyzing sales data in the food and beverages industry. The dashboard provides insights into consumer preferences, brand selection criteria, and purchase locations. It features interactive visualizations and filters to allow users to explore data based on specific parameters.

Worked on marketing campaign analysis to meet the KBR, Skills used were data cleaning using SQL, exploratory data analysis using Python, and dynamic dashboard creation using Tableau. Dashboard provides insights like exploring market trends, researching consumer behavior; analyzing sales and customer intent, measuring successful advertising campaign