Free IBM Cloud Pak for Data v4.x Solution ArchitectPractice Test
Test your knowledge with 20 free practice questions for the A1000-066 exam. Get instant feedback and see if you are ready for the real exam.
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Free Practice Questions
Try these IBM Cloud Pak for Data v4.x Solution Architect sample questions for free - no signup required
A financial services company wants to deploy IBM Cloud Pak for Data on their existing Red Hat OpenShift cluster. The cluster has 5 worker nodes with 16 vCPUs and 64 GB RAM each. Which consideration is MOST critical for the solution architect to evaluate first?
An organization has deployed Cloud Pak for Data and needs to implement data lineage tracking across multiple data sources including databases, object storage, and data pipelines. Which component should the solution architect recommend?
A solution architect is planning a Cloud Pak for Data deployment that requires high availability for critical analytics workloads. Which architectural approach best supports this requirement?
During implementation, a solution architect needs to configure storage classes for Cloud Pak for Data services. Some services require block storage while others can use file storage. What is the BEST practice for this scenario?
A data science team wants to collaborate on machine learning models using notebooks and needs to share compute resources efficiently. Which Cloud Pak for Data capability should be configured?
An enterprise is implementing data privacy controls and needs to mask sensitive customer information in production datasets used for analytics. The masking rules must be consistent across all consumption points. What is the recommended approach?
A solution architect is designing a multi-tenant Cloud Pak for Data environment where different business units need isolated access to data and services. Which architectural pattern best addresses this requirement?
During a Cloud Pak for Data upgrade, the solution architect needs to ensure minimal downtime for critical services. What is the recommended upgrade strategy?
A machine learning model deployed in Cloud Pak for Data is exhibiting bias in its predictions. Which service should be used to detect and monitor this bias?
An organization has compliance requirements mandating that all data access and modifications be auditable. How should the solution architect configure Cloud Pak for Data to meet this requirement?
A company needs to integrate Cloud Pak for Data with their existing LDAP-based enterprise directory for user authentication and authorization. What is the correct implementation approach?
A data architect needs to ensure that sensitive healthcare data in Cloud Pak for Data complies with regulatory requirements for data classification and access controls. Which combination of capabilities should be implemented?
A solution architect is planning network architecture for Cloud Pak for Data that will access data sources in multiple availability zones and on-premises data centers. What connectivity considerations are MOST important?
A development team wants to use AutoAI to automatically build and compare machine learning models for a classification problem. Which Cloud Pak for Data service provides this capability?
After deploying Cloud Pak for Data, users report intermittent connectivity issues when accessing the platform. The solution architect needs to troubleshoot. What should be the FIRST diagnostic step?
An organization wants to implement a data virtualization layer to provide unified access to data across multiple heterogeneous data sources without moving the data. Which Cloud Pak for Data service addresses this requirement?
A solution architect is designing a disaster recovery strategy for Cloud Pak for Data. Which components are MOST critical to include in the backup and recovery plan?
A company wants to enforce that all datasets containing personally identifiable information (PII) are automatically tagged and subject to specific access policies. How should this be implemented in Cloud Pak for Data?
A solution architect needs to optimize Cloud Pak for Data performance for compute-intensive machine learning workloads. Which architectural consideration would provide the MOST benefit?
An organization has deployed multiple machine learning models in production and needs to ensure model quality over time by detecting model drift and performance degradation. What Cloud Pak for Data capability should be configured?
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