A restaurant analytical tool + sales forecasting model

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.

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.

Sales dashboard using MS Excel

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

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

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

Tableau Visualizations

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

Done during a Data Visualization course, cleaned up a dataset so that the data is in a more readable and usable format.

Data Analyst Portfolio Project 4 - SQL - Analysing the Awesome Chocolates dataset with a wide variety of SQL queries

To create a forecast model using R that accurately predicts sales and demand for Walmart, incorporating factors like economic conditions and the effects of promotional markdowns and holidays.

This project was created as part of the Udemy course completion and aims to demonstrate the application of Power BI for in-depth sales data analysis.

An beginner exploratory data analysis project on Boat Sales.

📈 Open Cults3D CSV sale data files, view the processed data, and export a detailed statistical report.

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

Deriving key insgihts from Amazon Sales Data through data visualization using Python Libraries

Interactive Excel Dashboard for Coffee Sales Analysis: This project leverages Excel to analyze sales data, uncover seasonal trends, regional preferences, and customer behaviors, providing actionable insights for optimizing inventory and marketing strategies.

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.