A data analytics project using Python and Jupyter that explores and visualizes sales performance. Includes data cleaning, trend analysis, and meaningful business insights with charts and reports. Ideal for showcasing real-world data analysis skills.

AdventureWorks is a fictitious multinational manufacturing company. The data set used for this report is from the AdventureWorks2014 version. The goal of this project is to demonstrate how building powerful and beautiful (I hope :)) reports in Power BI by following the data visualization best practices and the data modelling patterns, showing the awesome features of Power BI like Report Page Tooltip, Calculated Groups, Forecasting, What-If parameters, Time Intelligence Functions, complex DAX code, custom charts and how it is easy to integrate Power BI with Python/R script in order to build machine learning models and so creating advanced and predictive analytics reports. Reports Pages are as follow: - P&L Overview: Profit & Loss Report, in which I analyzed the economic status of the company from the point of view of Revenues and Expenditures. In this report page I compared the trend of actual amount and budget amount, unfortunately for 2011 year only (missing data for other years). You can notice the powerful feature of “report page tooltip” in this page, by hovering over the bar charts. - Internet Sales Overview: in this report page I analyzed the sales of products to customers via Internet. You can notice the forecasting feature of Power BI and the use of what-if parameters in order to build advanced analytics reports. Also I made use of calculated groups (for further info about visit https://www.sqlbi.com/articles/introducing-calculation-groups/). - Reseller Sales Overview: similar to the previous one, but this time the focus is on the sales of products to resellers. Things to notice in this report page are the comparison of current sales vs last year sales, the comparison of actual sales amount vs budget/quota sales amount, and the running total and moving/running average charts. - Product Inventory Overview: inventory management analysis of the company. I analyzed the current stock on hold vs the recent sales revenue, showing the value of current stock, the current units in stock and the stock ratio. - Products Overview: in this report page I analyzed the products by category, color, size, “ABC” class too. Two very interesting and powerful things to notice: the basket analysis using DAX and the basket/association rules analysis using R script and apriori machine learning model. I made use of the custom chart called “Network Chart” to represent the association rules between products. Through the basket analysis the user could know which product is likely to be bought with another one. - Customers Overview: customer analysis by age group, location, status, and so on. The customer could be classified as “Bike Buyer” and “Non Bike Buyer”. So I decided to build a machine learning model (in this case I used XGBoost algorithm in Python) in order to predict if a (new) customer would be a bike buyer or not. The model has a prediction accuracy of about 84% which it is not bad. - Employees Overview: employee analysis by sales location, title, age. Thing to notice is the ribbon chart through which I can analyze the performance of employees over time. - Reseller Overview: analysis of the performance of the resellers. Important dimensions to analyze are the business type, the product line, the reseller location.

Data Analytics Project with the theme "Analysis of E-Commerce Sales Performance" using React and Laravel

This repository contains the data and Power BI dashboards for the Maven Sales Challenge, where I analyzed B2B sales opportunities and visualized key insights. The project includes sales team performance analysis, product performance metrics, account analysis, and sales forecasting. Explore the repository to delve into the world of sales analytics!

Power BI data analytics project on Pakistan’s largest e-commerce dataset, featuring interactive dashboards for sales performance, customer insights, payment analysis, and strategic business recommendations.

A collection of Tableau projects showcasing data visualization and analytics skills. These projects cover various domains, including sales analysis, business insights, customer trends, and performance tracking, providing interactive dashboards for data-driven decision-making.

A comprehensive business intelligence solution for e-commerce analytics, demonstrating advanced SQL querying techniques combined with Python data analysis. This project analyzes customer behavior, sales performance, and business metrics to derive actionable insights.

This is an interactive data analytics dashboard built with Python and Streamlit, using Brent Superstore dataset. This project provides real-time business insights through visualizations like sales trends, regional performance, profit analysis, customer segments, and discount impact.

This project performs an exploratory data analysis (EDA) on a simulated sales dataset to uncover key insights into sales performance, product trends, regional contributions, and customer segments. The goal is to provide a clear, visual understanding of sales data to support business decisions. Features

An Data Analytics End-to-end retail sales performance analysis Project using SQL, Python (Pandas) and Power BI to track regional revenue, product performance, repeat customers and key KPIs for data-driven business decisions.

data analytic project showcasing sales performance analysis using excel and power bi

End-to-end Excel data analytics project with an interactive dashboard for Vrinda Store sales performance analysis.

Business Sales Performance Analytics project focused on identifying revenue trends, top-performing products and regional performance using data analysis and visualization tools.

ETL-based Sales Analysis project that extracts, cleans and transforms raw sales data to generate business insights and performance indicators for analytics and reporting.

📊 Advanced Sales & Performance Analytics Dashboard This project demonstrates end-to-end sales and performance analysis, leveraging Power BI with Power Query, DAX, and optimized Data Modeling. Insights include sales trends, profitability, customer behavior, and managerial performance.

Retail Store Analysis is a data analysis project that explores retail sales data to uncover insights about customer behavior, product performance, and revenue trends using data analytics and visualization techniques.

SQL-based data analytics project covering end-to-end analysis on sales data, including segmentation, KPIs, performance tracking, and reporting views for customers and products.

A data analytics project that explores retail sales data using Python, Pandas, and Matplotlib to uncover trends, regional performance, and profit insights through exploratory data analysis and visualization.

Sales Analysis Project using PySpark 📊: Explore sales data, visualize insights, and analyze key performance indicators (KPIs) with PySpark. Includes code and Databricks notebook. Dive into business analytics! 💼💡

Cafe Sales Analysis Project A data analysis project using Excel, SQL, and Python to analyze cafe sales data. The project covers data cleaning, exploratory analysis, and insights generation on sales trends, product performance, and revenue patterns. Designed to demonstrate end-to-end data handling and analytical skills across multiple tools.

Retail Sales Data Analysis 📊 This project analyzes retail transactions to uncover sales trends, promotion impacts, and store performance** using **data visualization & analytics**. Key insights: **Winter sales peak, Buy One Get One” boosts transactions, and supermarkets lead sales—guiding strategic decisions. 🚀

This Pizza Sales Analysis project aims to provide valuable insights into pizza sales performance using data analytics techniques. The project involves cleaning, visualizing, and analyzing sales data to identify patterns and trends that can help optimize business strategies tools using powerbi and sql.

The Restaurant Sales Analysis project from Maven Analytics is a guided Project which focuses on analyzing transactional data from a restaurant to uncover insights about sales performance, customer behavior, and product trends with EDA

A SQL-based data analysis project on Walmart sales data. It includes queries to analyze sales trends, customer behavior, product performance, and store-level insights. Designed to practice SQL analytics and support data-driven retail decision-making.

RetailIQ Pulse is an end-to-end retail performance analytics project focused on analyzing customer behavior, product performance, regional trends, and time-based sales insights using structured data analysis to support data-driven business decisions.

Data Analysis Project: Superstore Performance.Data analytics project focused on translating raw sales data into actionable business insights. Key Skills Demonstrated: Data cleaning, KPI calculation, time-series analysis, comparative visualization (pie charts, bar charts). Tools Used (Customize this): Power BI / Python (Pandas, Matplotlib)

This project demonstrates a data-driven sales analysis of Walmart stores using SQL. It applies real-world data analytics techniques to uncover insights into store performance, customer behavior, and category-wise sales trends — all using pure SQL.

Comprehensive Data Analytics project encompassing SQL Server database design, automated ETL processes using stored procedures, and the creation of strategic dashboards for global sales performance analysis in 2023.

E-commerce Sales Data Analysis project using the "Analyzing and Maximizing Online Business Performance" dataset from Kaggle. Includes data cleaning, manipulation, descriptive analytics, and visualizations to optimize profitability and operational efficiency.

A fully interactive analytics dashboard that provides insights into retail sales performance, customer behavior, and business growth trends. This project demonstrates practical end-to-end data analytics: cleaning, modeling, analysis, DAX, visualization, and storytelling.