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[General] Newly C1000-173 Exam Dumps [2026] For Massive Achievement

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【General】 Newly C1000-173 Exam Dumps [2026] For Massive Achievement

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q108-Q113):NEW QUESTION # 108
What is a key method to achieve multi-tenancy within a single instance of Cloud Pak for Data?
  • A. Utilizing shared namespaces for all tenants
  • B. Utilizing shared namespaces for all tenants
  • C. Combining data from all tenants
  • D. Ignoring resource quotas
Answer: B

NEW QUESTION # 109
When upgrading to Cloud Pak for Data v4.7, why must an export/import of governance data be performed?
  • A. Components of Information Server have been removed from the product.
  • B. Catalog data must be relocated to persistent storage.
  • C. Containers are ephemeral and cannot persist the data.
  • D. The underlying Db2 repository has been altered.
Answer: D
Explanation:
During the upgrade to Cloud Pak for Data version 4.7, significant changes were made to the underlying metadata repository, which is powered by Db2. These changes affect how governance data is stored and accessed, and an export/import is necessary to ensure compatibility and data integrity. The export step extracts governance metadata using the supported utility, and after the upgrade, it is re-imported into the upgraded structure. This is not due to container ephemerality or storage changes, but because of schema and format changes in Db2.

NEW QUESTION # 110
What does Watson OpenScale require to generate statistics?
  • A. Test data subset (10%)
  • B. Access to Pipeline
  • C. Complete test data set
  • D. Training data
Answer: D
Explanation:
* Training Data Statistics:Watson OpenScale needs to understand the characteristics of the data the model was trained on. This includes things like the distribution of features, sensitive attributes (for fairness monitoring), and how the model performed on this initial data. These "training data statistics" are crucial for:
* Fairness Configuration:Recommending fairness attributes, reference, and monitored groups.
* Bias Detection:Calculating fairness metrics (like disparate impact) by comparing runtime behavior to the learned training data distribution.
* Explainability:Generating explanations by understanding the distribution of values in the training data to create meaningful perturbations.
* Drift Detection:Building a drift detection model that compares runtime data to the training data to identify shifts.
While Watson OpenScale also consumespayload data(the data sent to the deployed model for predictions) at runtime to calculate various metrics and perform monitoring, the initial setup and the ability to generate meaningfulstatisticsfor things like fairness and drift fundamentally rely on understanding thetraining data

NEW QUESTION # 111
Which of the following statements best describes the business value of Watson Assistant?
  • A. It provides enhanced security for cloud-based services.
  • B. It offers an advanced platform for numerical computation.
  • C. It significantly reduces the time required for data processing.
  • D. It improves customer engagement through AI-driven conversations.
Answer: D

NEW QUESTION # 112
How does the IBM Data Virtualization service virtualize files in shared directories?
  • A. It scans its network for open file shares.
  • B. A remote connector is installed and run on the source server.
  • C. Users add shared file systems in the UI.
  • D. Administrators configure FTP connections to the file source.
Answer: B
Explanation:
To virtualize files that reside in shared directories (e.g., NFS, SMB, or other on-premises sources), IBM Data Virtualization uses a remote connector agent. This remote connector is installed and executed on the source server to enable secure access and metadata extraction. The service does not scan networks automatically nor rely on FTP. Directly adding file shares via the UI is not sufficient without the backend connector in place, which acts as a secure communication bridge.

NEW QUESTION # 113
......
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