Title: Nashville Housing Data Cleaning Using SQL
Description/Problem Statement: The Nashville housing dataset exhibited inconsistencies and discrepancies across various fields, including date formats, address parsing, and null values, hindering effective analysis and decision-making. Solution: Employed advanced SQL techniques to address data inconsistencies:
- Standardized date formats using SQL Convert function.
- Parsed address, city, and state columns with Substring/ParseName functions.
- Imputed null values through self-joins with conditional logic.
- Standardized values using SQL Case Statements.
- Optimized dataset by dropping redundant columns with SQL Alter Drop commands.
- Removed duplicate rows using SQL Window functions.
Key Takeaways:
- Enhanced data integrity and reliability for improved analysis.
- Streamlined dataset for efficient processing and modeling.