SQL-Portfolio

Welcome to my SQL portfolio! This repository contains a collection of my SQL projects, showcasing my skills in data cleaning and exploratory data analysis (EDA). Each project includes detailed SQL scripts and explanations to demonstrate my approach and methodology.

Projects

• Project: Row Health Targeted Insights

  • Description: This project involved answering key business questions for a reimbursement program using SQL. Insights were derived on topics such as product claims, campaign performance, subscription trends, and customer behavior. The data was cleaned, transformed, and merged to create an analysis-ready dataset

  • SQL Skills Used: Data Aggregation, Date Handling , Window Functions, Common Table Expressions (CTEs), Joins, Filtering, Sorting, String Manipulation

  • Output: Created a clean and structured dataset for Excel analysis by combining three CSV files using SQL transformations.

  • Resources:

  • View Insights SQL Script:

  • SQL Script for Excel analysis

  • More Detailed Insights:

• Project: Contoso

  • Description: Project involves analyzing customer behavior, retention trends, and lifetime value for an e-commerce company

  • SQL Skills Used: Table Creation,Common Table Expressions (CTEs), Window Functions, Aggregations, Group By, Joins, Date Functions.

  • Resources:

  • View SQL Scripts

  • Original dataset from here.

• Project: Northwind Traders

  • Description: This project involves cleaning and transformingc data to prepare it for analysis.

  • SQL Skills Used: Table Creation,Data Type Conversion, Common Table Expressions (CTEs),Date Functions,Joins, aggregations,window functions,Grouping and filtering for segmentation.

  • Resources:

  • View SQL Scripts

  • Original dataset from here.

• Project: Layoffs Analysis

  • Description: This project focuses on preparing and analyzing raw layoff data to uncover trends and insights related to workforce reductions from the onset of March 2020 to April 2025. The objective is to assess the scale, timing, and sector-wise distribution of layoffs across different sectors.

  • Key SQL Skills Applied: Data cleaning and transformation, data type standardization, use of Common Table Expressions (CTEs), string parsing, window functions for trend analysis, aggregations and grouping for summarization, table joins.

  • Resources:

  • View Data Cleaning SQL Script

  • View Exploratory Data Analysis (EDA) SQL Script