In this project we conduct data cleaning and data exploration of housing data.

Skills used: JOINS, String Functions, Window Functions, ISNULL Functions, CASE Statements, CTE's, Aggregate Functions, Aliases, Rank, Count, Slicing Data using NTILE

Data Cleaning in SQL

• Using CONVERT function, we standardised the date format
• Populated the property address 
• Broke out address into individual columns (address, city, state) using SUBSTRING and CHARINDEX with the comma delimiter as well as using PARSENAME with REPLACE
• Changed Y and N to ‘YES’ and ’NO’ to fit in line with the rest of the calculations in the table using CASE statements 
• Removed duplicates using Row number as CTE and Window function such as PARTITION BY
• Removed redundant columns