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| Section | Objectives |
|---|---|
| Topic 1: Cloud Pak for Data Architecture Overview | - Deployment architectures and environments - CP4D core platform components and services |
| Topic 2: AI and Machine Learning Lifecycle | - Watson Studio project lifecycle - Model development, training, and deployment workflows |
| Topic 3: Data Integration and Engineering | - Data ingestion pipelines and DataStage concepts - Data transformation and ETL/ELT workflows |
| Topic 4: Data Governance and Cataloging | - Watson Knowledge Catalog concepts - Data lineage, metadata management, and governance policies |
| Topic 5: Security, Operations, and Platform Management | - Identity and access management in CP4D - Monitoring, scaling, and operational best practices |
| Topic 6: Data Storage and Virtualization | - Data Virtualization services and query federation - Db2 and integrated storage options |
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NEW QUESTION # 43
Which Cloud Pak for Data service is used to cleanse and shape tabular data?
Answer: D
Explanation:
Data Refinery is the dedicated data preparation service in IBM Cloud Pak for Data. It enables users to cleanse, shape, filter, and enrich tabular datasets through a graphical interface. Users can create data preparation flows that integrate seamlessly with Watson Studio and other services. Data Manager and Data Wrangler are not services available in CP4D, and Watson Data is not a recognized component. Data Refinery is the officially supported tool for this purpose.
NEW QUESTION # 44
If a Cloud Pak for Data cluster is air-gapped, it is unable to reach the internet, and a private registry must be configured for installations and upgrades. Beyond container images, what other components need to be addressed?
Answer: C
Explanation:
In air-gapped (offline) environments, it's not just the container images that require preparation.
Package managers like pip (for Python) and other utilities commonly attempt to pull dependencies from public internet repositories. These must be redirected to internal mirrors or handled via offline bundles. If left unaddressed, certain operations within components like Jupyter notebooks, Watson Studio, or pipelines may fail. License validation and monitoring do not inherently require internet access, and data movement between nodes is part of normal cluster function--not something to be blocked.
NEW QUESTION # 45
What must be created to enable the Cloud Pak for Data platform to use a company's custom CA certificate to validate certificates from internal servers?
Answer: B
Explanation:
To enable IBM Cloud Pak for Data to trust certificates from internal servers using a custom Certificate Authority (CA), the correct method is to create a Kubernetes ConfigMap that contains the CA certificate. This ConfigMap is referenced by the platform's foundational services to include the CA in the trusted root store.
Secrets are typically used for storing sensitive data like private keys and TLS certificates but are not used for adding trusted root CAs at the platform level. A ConfigMap is explicitly required by the platform to inject the CA trust into the certificate validation chain.
NEW QUESTION # 46
Which option is supported for backing up and restoring Cloud Pak for Data on a FIPS-enabled cluster?
Answer: D
Explanation:
For Cloud Pak for Data deployed on a FIPS-enabled cluster, the supported method for backup and restore is the online backup and restore to the same cluster. This method ensures that the data and configuration remain compliant with FIPS encryption standards. Offline and cross-cluster restore methods are not supported under FIPS constraints due to strict requirements around key handling and encryption. The Snap and Restore Tool and Watson Backup Assistant are not applicable to this context.
NEW QUESTION # 47
Which of the following statements best describes the business value of Watson Assistant?
Answer: C
NEW QUESTION # 48
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