Historical Sales Using Price Elasticity to determine customer responsiveness to future price changes
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Updated
Jul 23, 2022 - Jupyter Notebook
Historical Sales Using Price Elasticity to determine customer responsiveness to future price changes
A restaurant analytical tool + sales forecasting model
A desktop application that uses Envato API to get sales data for Envato market Authors.
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 Exploratory Data Analysis & Visualization Using Python & Tableau public.
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.
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.
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.
Data Analyst Portfolio Project 4 - SQL - Analysing the Awesome Chocolates dataset with a wide variety of SQL queries
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.
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.
Deriving key insgihts from Amazon Sales Data through data visualization using Python Libraries
📈 Open Cults3D CSV sale data files, view the processed data, and export a detailed statistical report.
Done during a Data Visualization course, cleaned up a dataset so that the data is in a more readable and usable format.
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