Using Python Pandas Library to Analyze Sales Data
A Superstore management system made with JavaFX.
Superstore Sales and profit
Interactive Tableau dashboard for analyzing Superstore sales, profit trends, top products, customer segments, and regional performance.
Dashboard Superstore for Mid Term Visual Information Course Submission in Unsika 2024
SQL data analysis projects on various topics
SuperStore Business Intelligence Dashboard
This is my Power BI Project for the Master Program
Data Visualization and Storytelling
Executive-level Power BI dashboard built on the Superstore dataset using the .pbip project structure for version control and collaboration. Delivers quarterly sales insights across regions, product categories, and customer segments, with a clean semantic model and consistent design system.
An interactive Machine Learning web application built with Streamlit, featuring Time-Series Forecasting and Customer RFM Segmentation.
📊 Sales Analytics Dashboard built with Power BI — analyzing $2.30M in sales across regions, segments, categories & ship modes with dynamic slicers and DAX-powered KPIs.
Superstore sales analysis: EDA + KPI insights + profit prediction (XGBoost/RF) + Holt-Winters forecasting.
A Time Series Analysis and Forecasting, using ARIMA and Prophet models, on a superstore dataset.
Case Superstore desenvolvido no Power BI
📊 Exploratory data analysis of the Superstore dataset using Python, Pandas, NumPy, Matplotlib, and Seaborn. Analyzes sales, profit, customers, repeat purchases, shipping costs, country performance, and monthly order trends.
Power BI dashboard delivering Superstore sales analytics featuring interactive overview metrics, trend analysis, customer and product insights, regional rankings, key influencers and dynamic filters
Exploratory Data Analysis (EDA) of retail sales using Python (pandas, matplotlib, seaborn). Includes data cleaning, visualizations, and business insights.
The spark Foundation Internship-GRIP
Cleaned and transformed the Superstore Sales dataset using Python and Pandas to prepare it for interactive dashboarding and business insights.
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