Data Cleansing

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Multiple Choice

Data Cleansing

Explanation:
Data cleansing focuses on improving data quality by finding inaccuracies or irrelevant data and taking action to fix, standardize, or remove it. Encrypting data for security is about protecting information, not cleaning it. Archiving old data relates to storage and retention, not improving the quality of current data. Sorting data into folders is about organization and accessibility, not correcting data quality. In practice, data cleansing involves identifying duplicates, correcting misspellings or inconsistent formats, standardizing fields (like dates and addresses), validating values against business rules, and removing or updating invalid or out-of-range records. This process ensures the data are accurate, consistent, and reliable for analysis, reporting, and decision-making.

Data cleansing focuses on improving data quality by finding inaccuracies or irrelevant data and taking action to fix, standardize, or remove it. Encrypting data for security is about protecting information, not cleaning it. Archiving old data relates to storage and retention, not improving the quality of current data. Sorting data into folders is about organization and accessibility, not correcting data quality.

In practice, data cleansing involves identifying duplicates, correcting misspellings or inconsistent formats, standardizing fields (like dates and addresses), validating values against business rules, and removing or updating invalid or out-of-range records. This process ensures the data are accurate, consistent, and reliable for analysis, reporting, and decision-making.

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