A marketing team is building a model to predict customer lifetime value. They have data from multiple sources, including CRM, web analytics, and purchase history. What data quality standard is most critical to define?

Consistency across sources, ensuring customer IDs match

Completeness, requiring all fields to be filled

Timeliness, ensuring data is updated daily

Accuracy, requiring 100% correct values

A bank is building a credit risk model. The data team has collected a dataset with 200,000 loan applications. Before training, they need to establish acceptance criteria. Which criterion is most appropriate?

All records must be from the current year

The dataset must contain at least 500,000 records

The dataset must have a maximum of 10% missing values in any field

The dataset must be in JSON format

A retail chain wants to build a model to forecast store-level sales. They have transaction-level data from all stores. The model must be accurate for both high-volume and low-volume stores. What granularity should they specify?

Transaction-level data for all stores

PMICertified Professional in Managing AI (PMI-CPMAI)

Domain 3Objective 1

Define Required Data PMI-CPMAI Practice Questions (Page 4)

Part of the Identify Data Needs domain, which accounts for 26% of the PMI-CPMAI exam. PMI does not publish an official question count, but from its 160-minute exam (~65–105 total, ~17–27 in this domain), expect 2–3 from this objective — we provide 33 practice questions to prepare you well beyond it. (estimate)

33questions here

7free pages

9concepts

26%of the exam

Questions 16–20

16foundation · easy
Which sampling method selects every 10th record from a sorted list of customers?
Select an answer first
17foundation · easy
Which data structure is best suited for a model that predicts stock prices using daily closing values over several years?
Select an answer first
18application · medium
A marketing team is building a model to predict customer lifetime value. They have data from multiple sources, including CRM, web analytics, and purchase history. What data quality standard is most critical to define?
Select an answer first
19application · medium
A bank is building a credit risk model. The data team has collected a dataset with 200,000 loan applications. Before training, they need to establish acceptance criteria. Which criterion is most appropriate?
Select an answer first
20expert · hard
A retail chain wants to build a model to forecast store-level sales. They have transaction-level data from all stores. The model must be accurate for both high-volume and low-volume stores. What granularity should they specify?
Select an answer first

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Define Required Data PMI-CPMAI Practice Questions (Page 4)

Questions 16–20

Which sampling method selects every 10th record from a sorted list of customers?

Which data structure is best suited for a model that predicts stock prices using daily closing values over several years?

A marketing team is building a model to predict customer lifetime value. They have data from multiple sources, including CRM, web analytics, and purchase history. What data quality standard is most critical to define?

A bank is building a credit risk model. The data team has collected a dataset with 200,000 loan applications. Before training, they need to establish acceptance criteria. Which criterion is most appropriate?

A retail chain wants to build a model to forecast store-level sales. They have transaction-level data from all stores. The model must be accurate for both high-volume and low-volume stores. What granularity should they specify?

Keep studying — Identify Data Needs