A restaurant analytical tool + sales forecasting model

Historical Sales Using Price Elasticity to determine customer responsiveness to future price changes

A desktop application that uses Envato API to get sales data for Envato market Authors.

Synthetic sales data analysis with Python. Generate realistic sales transactions, clean and validate data, compute KPIs, and visualize revenue trends by day, month, and category. Includes reproducible scripts and charts for portfolio demonstration.

End-to-end demand forecasting with Python using synthetic time-series sales data. Includes data generation, cleaning, ARIMA/SARIMA model selection by AIC, evaluation with RMSE and MAPE, and 90-day forecasts with confidence intervals. Reproducible scripts and visualizations for portfolio showcase.

Anomaly detection in synthetic transaction and sales data with Python. Generates realistic data, injects unusual events, and applies Isolation Forest, Local Outlier Factor, and Z-score methods to detect outliers. Produces anomaly reports and visualizations for portfolio-ready demonstration of data science skills.

Using Python, Pandas & Matplotlib to analyze and answer business questions about 12 months worth of sales data. The data contains hundreds of thousands of electronics store purchases broken down by month, product type, cost, purchase address, etc.

This project performs advanced analysis of sales data across different company branches. It includes data cleaning, calculation of revenue and profit metrics, and visual comparison between branches.

Dashboard interativo de vendas do Xbox Game Pass, criado no Excel para análise e visualização de dados de assinaturas.

In this project, I analyze commercial sales data using NumPy and pandas. I visualize total revenue per product using color-coded bar charts in Matplotlib. It’s a foundational step in business data analysis and project documentation.

A MySQL server data was hooked with tableau, necessary data analysis, and data cleaning was performed. In the end, all the data was used to build interactive dashboards on Tableau.

📊 Análise Exploratória de Dados (EDA) avançada em vendas: padrões temporais, segmentação e automação com Pandas e Seaborn, preparando insights para Machine Learning.

This project analyzes customer segmentation and behavior using data science and cohort analysis. Key metrics like CRR, NRR, CLR, and CLV are examined through detailed charts, including the cohort layer cake and CLR vs. CLV cost efficiency analysis. Exploratory Data Analysis and systematic data manipulation reveal actionable insights.

SQL project analyzing sales data to identify top 3 Indian cities for Monday Coffee's physical store expansion.

Sales Exploratory Data Analysis & Visualization Using Python & Tableau public.

Data visualization of sales data every month, highest sales, lowest sales, and average sales

Criação de um Data Warehouse (DW) utilizando modelagem dimensional em um esquema estrela.

Power BI multi-page report leveraging advanced data visualization for RFM analysis. Delivers deep analytical insights into customer behavior, engagement, and spending patterns, driving strategic business decisions.

FinancialTrendAnalyzer helps analyze and visualize sales data to uncover financial trends. It uses Python to calculate total sales, track changes, and generate insightful charts for better decision-making.

This project involves analyzing a retail store's sales data using advanced SQL queries. It includes data extraction, transformation, and insightful analysis to uncover customer behavior, product performance, and seasonal trends. The analysis helps stakeholders make informed decisions based on revenue, customer segmentation, high-value transactions.