Associate Solution Architect of IBM Cloud Pak for Data: Learning Path Overview IBM Quiz Answers

Get Associate Solution Architect of IBM Cloud Pak for Data: Learning Path Overview IBM Quiz Answers

The IBM Cloud Pak for Data Solution Architect is a person who can design, plan, and architect a cloud solution. They can do this with limited assistance from support, documentation, and relevant subject matter experts.

This course is an introduction into the beginner-level path, which is one of three Learning Paths designed for solution architects of Cloud Pak for Data. In this course, you will find information about the courses that make part of this Learning Path, and you will get familiar with the use case that will be discussed in detail throughout the whole Learning Path.

You will need about 1 hour to complete this course.

Enroll on IBM

Quiz 1: Check for understanding

Q1. Which one of the following persona is a typical user of Cloud Pak for Data?

  • Telecommunications Specialist
  • Data Scientist
  • Information Analyst
  • Web Developer

Q2. True or false: Cloud Pak for Data is built on and takes advantage of the underlying resource and infrastructure optimization and management in Red Hat OpenShift Container platform.

  • True
  • False

Q3. How is the customer-managed Cloud Pak for Data platform that runs on any Cloud referred to?

  • Cloud Pak for Data on-premises
  • Cloud Pak for Data System
  • Cloud Pak for Data as a Service
  • None of the above

Q4. True or false: Cloud Pak for Data can be deployed on IBM Cloud only.

  • True
  • False

Q5. What are the key benefits of Cloud Pak for Data? (Select two.)

  • It provides insights into threats and risks and respond faster with automation across hybrid, multicloud environments.
  • It provides data governance
  • It enables you to automate network operations
  • It is a single, unified platform

Q6. How is building machine learning models in an automated way referred to?

  • AutoGovernance
  • AutoCatalog
  • AutoSQL
  • AutoAI
Conclusion:

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This Problem is intended for audiences of all experiences who are interested in learning about Data Science in a business context; there are no prerequisites.

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