Search results

Data Cleaning and Standardization

Overview:

To ensure high-quality and reliable data for further processing, the CSC data must be cleaned and standardized. This process helps improve data accuracy, consistency, and usability.

Transformations:

  1. Remove Duplicates: Identify and eliminate duplicate records based on unique identifiers (e.g., Customer ID, Ticket ID). Learn more about Removing Duplicates

  2. Null Value Handling: Replace null or missing values with predefined defaults or impute values based on averages (e.g., for customer ratings or service timestamps). Learn more about Null Value Handling

  3. Data Type Conversion: Ensure fields like dates, amounts, or customer ratings are in the correct format (e.g., converting text-based dates to a DATE format). Learn more about Data Type Conversion

  4. Remove Invalid Data: Filter out records with invalid or inconsistent data (e.g., negative ticket costs, invalid phone numbers). Learn more about Removing Invalid Data