Google Data Analytics Professional Certification Practice Test

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What is "clean data"?

Data that is complicated and difficult to analyze
Data that is complete and correct
Data that needs further validation
Data that has many redundancies

The correct answer is: Data that is complete and correct

Clean data refers to information that is accurate, consistent, and free from errors or inconsistencies. This means that the data must be complete; it should not have any missing values or inaccuracies. It also involves having a uniform format with no conflicting information, making it easy to analyze and derive meaningful insights from it. In contrast, complicated or difficult to analyze data would suggest issues with clarity or organization, which does not align with the concept of "clean" data. Data needing further validation indicates that there are potential inaccuracies or uncertainties, which again, detracts from being classified as clean. Data that has many redundancies would imply unnecessary repetition, reducing its efficiency and utility in analysis. Thus, clean data is best characterized as being complete and correct, enabling effective analysis and decision-making.