Using SQL for data cleansing and transformation

Data cleansing and data transformation are two main steps in the data preparation process. Data cleansing is the process of identifying and correcting errors in data, while data transformation is the process of converting data from one format or structure into another.

Here are some common examples of data cleansing tasks:

• Identifying and correcting typos
• Filling in missing values
• Formatting data consistently
• Removing duplicate records

Here are some examples of data transformation tasks:

• Converting data from one format to another
• Aggregating data (for example, summing sales figures by month)
• Normalizing data (for example, converting all dates into the same format)
• Formatting data for visualizations or machine learning

Now that you understand some scenarios where data cleansing and transformation would be useful, let’s look into some examples using SQL so that you understand...