
CertNexusCertified Data Science Practitioner (CDSP)
Domain 1Objective 2
Objective 1.2 Understand Challenges CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 4)
Part of the 1.0 Defining the need to be addressed through the application of data science domain, which accounts for 7-9% of the CERTIFIED-DATA-SCIENCE-PRACTITIONER exam.
40questions here
8free pages
11concepts
7-9%of the exam
Questions 16–20
- 16
A multinational corporation is building a global HR analytics platform that will process employee data from multiple countries, including EU member states. The data science team wants to centralize the data in a single data lake for analysis. The legal team has identified GDPR as the primary regulation for EU employee data. What is the most important governance consideration?
Select an answer first - 17
A US healthcare provider wants to build a predictive model for patient readmission risk using electronic health records (EHR) that include patient names, diagnoses, and treatment histories. The data science team plans to store the data in a shared analytics environment. What is the primary compliance requirement the team must address?
Select an answer first - 18
A multinational company operates in the EU, the US (including California), and other regions. It is building a global customer analytics platform that will process personal data from customers in all regions. What is the most important consideration for the data science team?
Select an answer first - 19
A health and fitness app company wants to use user health data (e.g., heart rate, sleep patterns) to build a personalized wellness model. The app is available in the EU and California. The company currently has a general privacy policy but no specific consent mechanism for health data. What is the most appropriate action?
Select an answer first - 20
A data science team is considering using a new deep learning approach for image classification. They have a small labeled dataset and want to determine if the approach can achieve at least 90% accuracy before investing in more data collection and infrastructure. What should the team do?
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