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.