Which of the following is an example of a data irregularity that a data scientist should detect and handle during cleaning?

A categorical variable with a balanced distribution of categories

A value that falls far outside the expected range for that variable

A column with all values present and no missing entries

A consistent date format across all records

Why is it important to monitor and improve the data cleaning process over time?

To reduce the need for data governance

To ensure the data cleaning process never changes

To adapt to new data patterns and maintain data quality

To eliminate the need for human oversight

What is the goal of applying risk and bias mitigation techniques during data cleaning?

To ensure the data is stored securely

To make the data easier to visualize

To reduce the likelihood of biased or unfair model outcomes

To increase the size of the dataset

Which of the following is an example of adhering to data governance rules during cleaning?

Skipping documentation to save time

Following a documented data quality standard for handling missing values

Using a personal judgment to decide which rows to delete

Changing data formats without approval

CertNexusCertified Data Science Practitioner (CDSP)

Domain 2Objective 2

Objective 2.2 Clean Data Sets CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 7)

Part of the 2.0 Extracting, Transforming, and Loading Data domain, which accounts for 17-25% of the CERTIFIED-DATA-SCIENCE-PRACTITIONER exam.

51questions here

11free pages

18concepts

17-25%of the exam

18 Concepts in This Objective

Identify and eliminate irregularities in data
Handle nulls
Remove duplicates
Correct corrupt values
Parse data
Check for corrupted data
Correct data format
Deduplicate data
Apply risk and bias mitigation techniques
Understand common forms of ML bias
Identify sources of bias
Use exploratory data analysis for outlier detection
Assess data quality
Use data auditing techniques
Mitigate bias impact
Evaluate bias outcomes
Monitor and improve data cleaning process
Adhere to data governance rules

Questions 31–35

31foundation · easy
Which of the following is an example of a data irregularity that a data scientist should detect and handle during cleaning?
Select an answer first
32foundation · easy
Why is it important to monitor and improve the data cleaning process over time?
Select an answer first
33foundation · easy
What is the goal of applying risk and bias mitigation techniques during data cleaning?
Select an answer first
34foundation · easy
Which of the following is an example of adhering to data governance rules during cleaning?
Select an answer first
35application · medium
A model is being built to predict loan defaults. The training data was collected by a mobile app that is primarily used by younger, tech-savvy individuals. The model will be deployed to evaluate loan applications from the entire adult population. What type of bias is most likely present in this scenario?
Select an answer first

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