/SQL

This repository contains some complex, nested queries and important concepts of SQL using different kinds of enormous data.

Primary LanguageJupyter Notebook

SQL

This repository contains some complex, nested queries and important concepts of SQL using different kind of enormous data.

1. Manufacturing Process

Goal

The project's goal was to implement Statistical Process Control (SPC) to monitor and control the manufacturing process by analyzing data. The objective was to create an alert system that flags deviations in product height, ensuring the process stays within defined control limits.

Skills

SQL: Advanced querying, window functions, nested queries.

Results and Insights

  • Successfully created an alert system to detect products outside control limits.
  • Enhanced process quality by identifying deviations in real-time.
  • Delivered actionable insights for process adjustments and operator performance improvements.

Business Relevance

  • Quality Assurance: Ensured consistent product quality by monitoring process control limits.
  • Efficiency: Automated detection of process deviations, reducing the need for manual inspection.
  • Data-Driven Decisions: Provided a foundation for informed process adjustments, enhancing overall manufacturing efficiency and operator performance.

2. SQLCovidData.sql

  • There are two tables used for designing queries i.e. CovidDeaths and CovidVaccinations.

  • CovidDeaths contain following columns:

  • CovidDeathColumns

  • CovidVaccinations contain following columns:

  • CovidVaccineColumn1

  • CovidVaccineColumn2

  • Written down some queries using some columns from both the tables to get some useful information.

3. DataCleaninginSQL.sql

  • Used NashvilleHousing data to showcase some data cleaning techniques.