Data Cleaning with Microsoft SQL

Domain : Real Estate Industry

Function : Clean and transform the dataset for consistency, accuracy, and ready for analysis.

Problem Statement :

The Housing dataset is not clean and consistent, which makes it challenging to analyze and extract valuable insights. The dataset may contain errors, inconsistencies, and missing values, which need to be addressed before the data can be used for analysis.

Objective:

Clean and transform the dataset so that it is accurate, complete, and consistent. The cleaned dataset will be ready for analysis, and we can extract valuable insights from it to make better-informed decisions in the real estate industry.

Methodology :

The methodology involves several stages of data cleaning. We will use MS SQL Server to perform the following stages using SQL queries, stored procedures, and other features of MS SQL Server.

  • Data Profiling : Identifying inconsistencies, errors, and missing values.
  • Data Validation : Checking the data against predefined rules.
  • Data Cleansing : Correct errors and inconsistencies in the data.
  • Data Enrichment : Splitting and adding new information to the dataset, such as geospatial data or demographic data.

    • SQL-Queries Documentation