Which statement regarding data preparation in the ML workflow is correct?

The correct answer is C. One challenge of data gathering is obtaining high-quality data from multiple sources. The ISTQB CT-AI syllabus describes theML data preparation workflowin Section2.2 - Data Preparation. Data preparation consists ofdata gathering,cleaning, transformation, andsampling. The syllabus emphasizes that one significant challenge duringdata gatheringis combining data…

Machine Learning (ML)

Question

Options

AA key challenge in data transformation is the removal or correction of erroneous data.
BSince data preparation is time-consuming, all steps should be automated.
COne challenge of data gathering is obtaining high-quality data from multiple sources.
DSampling is so well researched that it is no longer considered risky.

How the community answered

(25 responses)

A
12% (3)
B
4% (1)
C
80% (20)
D
4% (1)

Explanation

The ISTQB CT-AI syllabus describes theML data preparation workflowin Section2.2 - Data Preparation. Data preparation consists ofdata gathering,cleaning, transformation, andsampling. The syllabus emphasizes that one significant challenge duringdata gatheringis combining data frommultiple heterogeneous sources, which often differ in structure, quality, and format. Ensuring the resulting dataset is accurate, complete, and representative can be complex, making this a critical challenge in the ML workflow. This aligns directly with Option C.

Topics

#data preparation#data gathering#data quality#ML workflow

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