yashdixitar2003-create/Algerian-Forest-Fire-Prediction

This project uses machine learning to predict forest fire areas using meteorological data from Algeria. The best performing model was Ridge Regression. # 🛒 Retail Sales & Profit Analysis Dashboard (Power BI + SQL) This project analyzes a retail dataset (Superstore) to uncover **sales and profit trends**, **state-wise losses**, and **top-performing customers** using SQL and Power BI. It simulates a real-world data pipeline with an end-to-end analytics approach. --- ## 📁 Project Structure | Component | Description | |----------|-------------| | `Sample - Superstore.csv` | Raw data (Orders, Sales, Profit, Region, etc.) | | `superstore_dashboard.pbix` | Power BI report file (includes data + visuals) | | `superstore.sqbpro` | SQLite database project | | `analysis_queries.sql` | SQL queries used for aggregation and preprocessing | | `dashboard_overview.png` | Screenshot of final dashboard | --- ## 📊 Key Features & Insights ### 🔥 Year-wise Profit Trend - 📈 Profit increased consistently from **2014 → 2017** - Peak profits in **Q4 2017** ### 🗺️ State-Level Analysis - ❌ **Top Loss-Making States**: - Texas: ₹-25,729 - Ohio: ₹-16,971 - Pennsylvania: ₹-15,559 - ✅ **Top Profit States**: - California: ₹76,381 - New York: ₹74,038 - Washington: ₹33,402 ### 👥 Customer Segmentation - Identified **Top 10 Customers** by total sales - Insights can guide loyalty or upsell campaigns ### 🎛️ Interactive Filters - Slicers for **Year** and **Category** help dynamic filtering - Charts and KPIs update in real-time based on user input ### 📌 KPI Summary Cards - 📦 Total Orders - 💸 Total Sales - 💰 Total Profit - 👥 Total Unique Customers --- ## 📷 Dashboard Preview --- ## 🛠️ Tools & Technologies - **SQL (SQLite Studio)** – Data cleaning and aggregation - **Power BI Desktop** – Visual analytics and dashboarding - **DAX** – Custom calculated columns (e.g., Year extraction) - **Data Modeling** – Relationships between tables, slicers - **Excel/CSV** – Raw data input --- ## 📂 How to Use 1. Clone or download this repository 2. Open `superstore_dashboard.pbix` in Power BI Desktop 3. Apply filters or explore different charts 4. Open `ana …