The data cleansing process typically involves the following steps:
Data Auditing: Assessing the dataset to identify errors and inconsistencies. Data Standardization: Ensuring that data follows a consistent format. Data Deduplication: Removing or merging duplicate records. Data Enrichment: Adding missing information to records. Data Validation: Verifying the accuracy and completeness of data. Data Transformation: Converting data into a usable format.