Azure Data Scientists Associate Practice Exam

What can the chip values component do with data values that exceed specified thresholds?

1. Replace them with a mean or constant value

2. Delete the values permanently

3. Highlight the values for review

4. Store them in a separate archive

The correct answer is: Delete the values permanently

The functionality of the chip values component is primarily designed to manage data values that exceed specified thresholds effectively. The correct choice suggests that these outlier values can be permanently removed. This action is practical in data processing because it helps in cleaning the dataset and ensuring that analysis results are not skewed by extreme values that can misrepresent trends or patterns. When values exceed defined thresholds, acknowledging them as outliers is crucial, but managing these outliers is equally important. By deleting these values, particularly if they are determined to be erroneous or irrelevant, the integrity of the data can be preserved for further analysis. The other options, while relevant in data processing contexts, do not align with the typical functionality and goals of the chip values component. Replacing with a mean may lead to loss of information or distort the original data distribution. Highlighting values for review does not resolve the issue immediately and could leave the dataset cluttered with potential outliers. Lastly, storing them in a separate archive, while useful for certain workflows, does not resolve the analysis of the main dataset and could complicate data retrieval later. Overall, the focus on removing problematic values ensures that the dataset remains robust and reliable for subsequent analysis.