A data team needs to build a model for a rare disease prediction. They have a small real dataset and access to a large public dataset of general health records. They are considering using synthetic data to augment the real dataset. What is the most important trade-off to evaluate?

The synthetic data may not capture the rare disease's specific patterns, leading to biased model predictions.

The public dataset is more accurate than synthetic data.

Synthetic data is always more expensive to generate than using public data.

Public data is always more privacy-compliant than synthetic data.

A data science team is building a model to predict housing prices. They have access to a large public dataset of property sales, but it lacks some features like proximity to schools. They also have a small proprietary dataset that includes those features. They need to improve model accuracy without violating data licensing. What should they do?

Combine the public dataset with the proprietary dataset, ensuring compliance with both licenses.

Use only the public dataset and ignore the proprietary data to avoid licensing issues.

Generate synthetic data to replace the proprietary dataset.

Use only the proprietary dataset and ignore the public data.

A student is working on a project that requires demographic data for a specific region. They want to use public data. What is the best way to access this data?

Use the official statistics bureau's website for the region.

Scrape data from social media platforms.

Generate synthetic data based on assumptions.

Which scenario is a typical use case for generated data?

Using government census data to study population growth

Purchasing a commercial dataset from a vendor

Creating a fake dataset to train a model without exposing customer PII

Analyzing website clickstream logs to understand user behavior

Which of the following is a common application of public data?

Testing software with fabricated user profiles

Monitoring internal system performance logs

Analyzing demographic trends using census data

Storing confidential customer records

CompTIADataX

Domain 4Objective 2

Data Types DY0-001 Practice Questions (Page 5)

Part of the Operations and processes domain, which accounts for 22% of the DY0-001 exam. CompTIA does not publish an official question count, but from its 165-minute exam (~65–110 total, ~14–24 in this domain), expect 2–3 from this objective — we provide 32 practice questions to prepare you well beyond it. (estimate)

32questions here

7free pages

8concepts

22%of the exam

Questions 21–25

21expert · hard
A data team needs to build a model for a rare disease prediction. They have a small real dataset and access to a large public dataset of general health records. They are considering using synthetic data to augment the real dataset. What is the most important trade-off to evaluate?
Select an answer first
22expert · hard
A data science team is building a model to predict housing prices. They have access to a large public dataset of property sales, but it lacks some features like proximity to schools. They also have a small proprietary dataset that includes those features. They need to improve model accuracy without violating data licensing. What should they do?
Select an answer first
23application · medium
A student is working on a project that requires demographic data for a specific region. They want to use public data. What is the best way to access this data?
Select an answer first
24foundation · easy
Which scenario is a typical use case for generated data?
Select an answer first
25foundation · easy
Which of the following is a common application of public data?
Select an answer first

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