🗄️ SQL for Data Engineering

This repository demonstrates my SQL skills applied in both real-world data engineering workflows and practice queries. It includes a Capstone Project highlighting end-to-end SQL-driven data transformation and practice exercises for mastering key SQL concepts.

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📂 Repository Structure

• Capstone_Project/ → Contains SQL scripts for an end-to-end data engineering project, including data transformation.
• SQL_Practicefiles/ → Contains SQL practice queries covering basics to advanced topics.

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🛠️ Skills & Concepts Demonstrated

• Data Extraction & Transformation

  • Writing optimized queries to join, clean, and filter raw datasets
  • Building reusable Views for downstream analytics
  • Applying Window Functions (ROW_NUMBER, RANK, LAG, LEAD)

• Data Modeling & Aggregations

  • Summarizing business KPIs (revenue, orders, growth rates)
  • Creating CTEs & Subqueries for modular design
  • Designing layered queries for staging and final analytical views

• Advanced SQL for Data Engineering

  • Using PIVOT / UNPIVOT for reshaping datasets
  • CROSS APPLY and OUTER APPLY for subquery joins
  • Implementing Stored Procedures for repeatable logic
  • Applying query optimization techniques for performance

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⚡ Example Queries

1. Customer Retention Analysis (Window Function)

SELECT 
    CustomerID,
    OrderDate,
    LAG(OrderDate) OVER (PARTITION BY CustomerID ORDER BY OrderDate) AS PreviousOrderDate,
    DATEDIFF(DAY, LAG(OrderDate) OVER (PARTITION BY CustomerID ORDER BY OrderDate), OrderDate) AS DaysBetweenOrders
FROM Orders;