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H13-311_V3.5 · Question #147

What are the common types of dirty data?

The correct answer is A. Malformed value B. Duplicate value C. Logically wrong value D. Missing value. All four options are correct because they represent the four fundamental categories of dirty data encountered in data quality management. A (Malformed value) refers to data that doesn't conform to expected format or structure - like a phone number stored as "abc-123" or a date…

Machine Learning Basics

Question

What are the common types of dirty data?

Options

  • AMalformed value
  • BDuplicate value
  • CLogically wrong value
  • DMissing value

How the community answered

(33 responses)
  • A
    100% (33)

Explanation

All four options are correct because they represent the four fundamental categories of dirty data encountered in data quality management.

A (Malformed value) refers to data that doesn't conform to expected format or structure - like a phone number stored as "abc-123" or a date as "32/13/2025". B (Duplicate value) occurs when the same record appears multiple times, skewing analysis and inflating counts. C (Logically wrong value) describes data that is syntactically valid but semantically impossible - such as a person's age being -5 or a birth date in the future. D (Missing value) covers null, blank, or placeholder entries where data was never captured or was lost.

There are no distractors here - this is an "all of the above" question where every option is a recognized dirty data type.

Memory tip: Use the acronym MDLM - Malformed, Duplicate, Logically wrong, Missing - or think of it as four ways data can go wrong: wrong shape, wrong count, wrong logic, wrong presence.

Topics

#data quality#dirty data types#data cleaning#data preprocessing

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