SQL | Data_wareHouse /Project

Data Warehouse and Analytics Project

Welcome to the Data Warehouse and Analytics Project! 🚀
This project demonstrates a full-stack data warehousing and analytics solution—from building the warehouse to generating actionable business insights. Designed as a portfolio project, it highlights best practices in data engineering and analytics.

Description:
sql-data-analytics-project is a comprehensive collection of SQL scripts for data exploration, analytics, and business intelligence reporting. This project provides ready-to-use SQL queries for various analytical needs, including:

  • Database exploration: Discover tables, schemas, and relationships.

  • Measures and metrics: Calculate sales, customer activity, product performance, and more.

  • Time-based trends: Analyze data over days, months, quarters, or years.

  • Cumulative analytics: Evaluate growth and trends using cumulative calculations.

  • Segmentation: Group customers and products by behavior, demographics, and performance.

  • KPI reporting: Generate key metrics for business dashboards and decision-making.

Each script is focused on a specific analytical goal and follows SQL best practices for clarity, efficiency, and maintainability. This repository is designed to help data analysts, BI professionals, and learners quickly perform complex analyses and accelerate their data projects.

Data -Analytics-Project

Truck Logistics Dashboard

An interactive analytics dashboard built with Streamlit, Pandas, and Plotly.
It helps track truck trips, distances, fuel usage, and product deliveries from an Excel file.

Features
  • Upload your Excel file with trip data (.xlsx)

  • Filter by Driver, Product, or Destination

  • View Key Metrics:

    • Total Distance (km)

    • Total Fuel Used (L)

    • Total Net Weight (kg)

    • Total Trips

  • Interactive Charts:

    • Distance by Driver & Product (Bar Chart)

    • Product Weight Distribution (Pie Chart)

    • Fuel Consumption Over Time (Line Chart)

  • Browse detailed trip data in a dynamic table