SindiAI / Data-Cleaning-and-Exploration-Project

Welcome to our data exploration and cleaning repository, where we delve into the intricacies of COVID-19 dataset and Nashville housing data. This project aims to showcase different techniques to explore and clean the data using SQL.

Data Exploration & Cleaning Project 🚀

Welcome to this exciting data exploration and cleaning project, guided by none other than Alext the Analyst! 📊✨

Overview

This repository is dedicated to the dynamic journey of understanding and refining datasets using SQL for comprehensive exploration and cleaning. The primary focus lies on two key domains: COVID-19 Data and Nashville Housing Data.

Guided by Alext the Analyst 📈

Alext, your experienced guide in this data adventure, brings a wealth of knowledge in data analysis and exploration. Together, we'll leverage SQL to unravel insights and ensure our datasets are pristine for further analysis.

Purpose of the Project 🎯

1. COVID-19 Data Exploration 🌐

• SQL Exploration Techniques:
  • Utilize SQL queries to navigate through the COVID-19 dataset.
  • Uncover trends, patterns, and correlations within the data.
  • Apply aggregate functions to extract summary statistics.

2. Nashville Housing Data Cleaning 🧹

• SQL Cleaning Functions and Techniques:
  • Address non-uniform data using CASE statements.
  • Standardize data formats with the CONVERTfunction.
  • Employ filtering conditions to remove outliers.
  • Populate data using self join.
  • Break out columns using SUBSTRING and PASENAME functions.
  • Remove duplicates and drop unused columns.
  • Implement the ROW_NUMBER() function for data ranking.

Collaboration and Feedback 🤝

This project thrives on collaboration! Whether you're a seasoned analyst or a curious learner, your input is valued. Share your thoughts, suggest improvements, and let's innovate together! 🌟

Happy coding and exploring! 🚀✨