I utilized SQL to perform data cleaning for a housing organization called NashvilleHousing, applying a variety of SQL queries to ensure data accuracy and consistency. The cleaning process involved executing DELETE queries, ALTER TABLE queries, SELECT queries, CREATE queries, UPDATE queries, and employing window functions and Common Table Expressions (CTEs).
A key focus of the cleaning process was removing duplicates and using CASE statements to create a new column where ‘N’ represented ‘No’ and ‘Y’ represented ‘Yes.’ Additionally, I applied the PARSENAME function to replace unwanted symbols within the dataset, further enhancing its quality.
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