Interactive Streamlit dashboard visualizing sales data from Excel with dynamic filters and key KPIs.

No description available

No description available

MarketIQ is a full-stack Streamlit + SQL + Prophet dashboard for real-time business intelligence. It transforms raw sales data into KPIs, trend analytics, and six-month forecasts. With SQL-driven insights, dynamic filtering, and exportable reports, MarketIQ helps analysts visualize growth and predict performance instantly.

Superstore Sales with Streamlit is a data visualization and analysis project that uses the Streamlit framework to create an interactive web application for exploring and analyzing sales data from a superstore. This project aims to provide an easy-to-use interface for users to gain insights into sales trends, Sales performance, product performance,

A visually interactive AI-powered sales forecasting dashboard using Streamlit, Plotly, and Python. Visualize KPIs, trends, and export filtered data with ease.

streamlit dashboard to analyse data

Super store sales streamlit interactive dashboard

MarketIQ is a full-stack Streamlit + SQL + Prophet dashboard for real-time business intelligence. It transforms raw sales data into KPIs, trend analytics, and six-month forecasts. With SQL-driven insights, dynamic filtering, and exportable reports, MarketIQ helps analysts visualize growth and predict performance instantly.

Real-time retail analytics dashboard with Streamlit, Pandas, and ML anomaly detection — simulates live sales data, provides interactive insights, and detects unusual patterns.

No description available

This repository contains an interactive Superstore Sales Dashboard built with Streamlit, Pandas, and Plotly. It provides a Power BI-style interface featuring key performance indicators (KPIs), sales trend analysis, and category-wise visualizations, along with filters for date range, region, and product category. The project serves as a practical da

Streamlit app for demonstration of Quarterly Sales Metrics Dashboard

End-to-end retail sales analysis with SQL, Python & live Streamlit dashboard | Window functions, Plotly, deployed on Streamlit Cloud

Production-ready MLOps pipeline for sales prediction featuring experiment tracking with MLflow, automated model registry with quality gates, FastAPI prediction service, and Streamlit dashboard. Built with XGBoost, scikit-learn, and Docker.

Builds a full pipeline for retail sales forecasting using Prophet and EDA techniques. Includes data ingestion, cleaning, profitability analysis, and actionable recommendations. Features a Streamlit dashboard for insights and a FastAPI backend for deployment.

dashboard sales streamlit

No description available

No description available

No description available

This repository contains an interactive data visualization dashboard built using Streamlit, designed to explore and analyze the "Superstore" dataset. The dashboard allows users to upload their own dataset or use a default one to explore various sales metrics and insights.

Comprehensive analysis of coffee shop sales utilizing Pandas for data cleaning and exploratory data analysis (EDA), complemented by Streamlit for creating interactive data visualization dashboards.

Interactive sales & revenue dashboard built with Streamlit & Plotly on the Superstore dataset.

End-to-end retail analytics platform featuring sales aggregation, demand forecasting, price optimization, and an interactive Streamlit dashboard.

An automated business intelligence dashboard built using Python, Streamlit, and Machine Learning for data visualization and sales prediction.

A business intelligence dashboard built with Streamlit and Python that allows users to analyze retail sales data through KPIs, interactive charts, and real-time filtering.

my midterm project in Data Science at Epsilon AI, Amazon India sales data analysis project featuring comprehensive data cleaning, exploratory analysis, and interactive Streamlit dashboard.

Retail analytics platform with sales forecasting (Prophet), customer segmentation (K-means), and interactive dashboards. Built with Python, SQLite, and Streamlit for end-to-end data analysis.

A real-time CDC (Change Data Capture) simulation dashboard using SQLite to mimic ETL pipelines and visualize live sales data. Built with Streamlit and Plotly, includes multi-user login support.

AI-powered B2B sales platform built with Python & Streamlit. Features 3 ML models (70-85% accuracy), technology-based company search, automated lead scoring, and analytics dashboards. Processes 120+ companies with real-time predictions and CRM-ready exports. Helps sales teams find prospects 10x faster.