A financial institution is loading transaction data from a third-party vendor. The data dictionary specifies that the 'transaction_type' column should only contain 'DEBIT' or 'CREDIT'. During a quality check, an analyst finds values like 'debit', 'Debit', and 'CRDIT'. What is the most appropriate action?

Keep the values as they are, as they all represent the same categories.

Remove all rows that contain any value other than the exact strings 'DEBIT' or 'CREDIT'.

Replace all values that are not exactly 'DEBIT' or 'CREDIT' with a null value.

Standardize the values by converting to uppercase and correcting the obvious typo 'CRDIT' to 'CREDIT'.

Why is it important to correct data formats to a consistent standard?

To make the data more visually appealing

To comply with data privacy laws

To reduce the number of columns in the dataset

To ensure that data can be compared and analyzed correctly

How can data transformation introduce bias into a dataset?

By increasing the number of features

By sorting the data alphabetically

By applying a transformation that disproportionately affects certain groups

A data analyst is working with a dataset that contains a 'phone_number' column. The values are stored in various formats, such as '(555) 123-4567', '555.123.4567', and '5551234567'. The analyst needs to join this data with another table that uses the format '555-123-4567'. What is the most appropriate cleaning step?

Remove all non-numeric characters from the phone numbers.

Convert all phone numbers to a single integer type.

Keep the data as-is and perform the join using a fuzzy matching technique.

Standardize all phone numbers to a single format, such as '555-123-4567'.

A data engineering team has a nightly ETL pipeline that cleans and loads sales data. Recently, the source system started sending dates in a new format, causing the pipeline to fail. The team fixed the immediate issue, but wants to prevent this from happening again. What is the most effective long-term solution?

Document the date format change in the data dictionary.

Write a one-time script to correct the new date format in the existing data.

Stop using the date field from the source system.

Add a validation step in the pipeline that checks the date format and alerts the team if it changes.

CertNexusCertified Data Science Practitioner (CDSP)

Domain 2Objective 2

Objective 2.2 Clean Data Sets CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 9)

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 41–45

41application · medium
A financial institution is loading transaction data from a third-party vendor. The data dictionary specifies that the 'transaction_type' column should only contain 'DEBIT' or 'CREDIT'. During a quality check, an analyst finds values like 'debit', 'Debit', and 'CRDIT'. What is the most appropriate action?
Select an answer first
42foundation · easy
Why is it important to correct data formats to a consistent standard?
Select an answer first
43foundation · easy
How can data transformation introduce bias into a dataset?
Select an answer first
44application · medium
A data analyst is working with a dataset that contains a 'phone_number' column. The values are stored in various formats, such as '(555) 123-4567', '555.123.4567', and '5551234567'. The analyst needs to join this data with another table that uses the format '555-123-4567'. What is the most appropriate cleaning step?
Select an answer first
45expert · hard
A data engineering team has a nightly ETL pipeline that cleans and loads sales data. Recently, the source system started sending dates in a new format, causing the pipeline to fail. The team fixed the immediate issue, but wants to prevent this from happening again. What is the most effective long-term solution?
Select an answer first

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Objective 2.2 Clean Data Sets CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 9)

Questions 41–45

Why is it important to correct data formats to a consistent standard?

How can data transformation introduce bias into a dataset?

Keep studying — 2.0 Extracting, Transforming, and Loading Data