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Trustable IBM Testing C1000-173 Center and the Best Accurate Reliable C1000-173 Exam Simulator

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2025 Professional Testing C1000-173 Center | 100% Free Reliable IBM Cloud Pak for Data v4.7 Architect Exam Simulator

The IBM C1000-173 certification is on trending nowadays, and many IT aspirants are trying to get it. Success in the C1000-173 test helps you land well-paying jobs. Additionally, the IBM C1000-173 certification exam is also beneficial to get promotions in your current company. But the main problem that every applicant faces while preparing for the C1000-173 Certification test is not finding updated IBM C1000-173 practice questions.

IBM C1000-173 Exam Syllabus Topics:

Topic
Details

Topic 1

Architect with Data Governance Services: This section evaluates skills of a Data Governance Specialist, covering the architecture of knowledge catalogs to enable data discovery and management. Data Privacy architectures ensure compliance with regulatory requirements around data protection. Knowledge Accelerators involve designing solutions that speed up data governance processes through predefined policies and templates.

Topic 2

Plan for a Cloud Pak for Data Implementation: This section of the exam measures the skills of an Implementation Consultant and covers determining which Cloud Pak for Data services to deploy based on organizational needs. It involves sizing the Kubernetes
OpenShift cluster appropriately for workload demands and planning backup and restore strategies to ensure data protection. Planning for high availability and disaster recovery is essential to maintain uninterrupted service. Multi-tenancy requirements must be understood to support multiple user groups securely on shared infrastructure. Migration requirements need assessment to transition existing data and workloads smoothly.

Topic 3

Architect with Data Source Services: This domain measures expertise of a Data Integration Architect and includes architecting solutions with data replication technologies to synchronize data across systems. IBM Data Virtualization architecture enables access to and querying of disparate data sources without data movement. Architecting with watsonx.data focuses on building intelligent data lakes and query engines. Architecting with Db2-related services involves designing scalable data management and processing architectures using IBM's Db2 platforms.

Topic 4

Security Requirements: This domain targets a Security Architect and focuses on planning security for a Cloud Pak for Data deployment. It includes managing certificates that secure communications, identity management systems, and access and authorization controls to enforce secure and compliant user and service interactions. The auditing features and their integration with enterprise audit systems are crucial to ensure traceability and accountability. Asset interchange security involves safeguarding data movement between services.

IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q178-Q183):

NEW QUESTION # 178
Which Db2 Big SQL component uses system resources efficiently to maximize throughput and minimize response time?

A. Hive
B. Scheduler
C. StreamThrough
D. Analyzer

Answer: C

Explanation:
StreamThrough is a high-performance component used in Db2 Big SQL within IBM Cloud Pak for Data that is optimized to manage data streams and queries efficiently. It is designed to maximize throughput and minimize query response times by optimizing memory usage, resource allocation, and processing logic.
Unlike Hive or Analyzer, which are used for query execution and analysis, StreamThrough enables efficient pipeline execution by streamlining data handling. Scheduler is used for job timing but does not influence runtime efficiency directly. StreamThrough is purpose-built to enhance performance through optimal resource usage.

NEW QUESTION # 179
What does Watson OpenScale require to generate statistics?

A. Access to Pipeline
B. Training data
C. Test data subset (10%)
D. Complete test data set

Answer: B

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 # 180
A Cloud Pak for Data installation was initially deployed on Microsoft Azure via the automated deployment option. What can be used to upgrade the environment?

A. PowerShell
B. Command Line Interface (CLI)
C. Cloud Providers Marketplace
D. GitHub Repo

Answer: B

Explanation:
For environments deployed via automated cloud options (such as Azure or AWS), upgrades are performed using the Command Line Interface (CLI). The CLI allows administrators to pull the latest operators, update foundational services, and upgrade installed services. The cloud marketplace is used only for initial provisioning, not for upgrades. PowerShell and GitHub repositories are not used as upgrade mechanisms within the official CP4D deployment lifecycle.

NEW QUESTION # 181
Why is tethering projects to the IBM Cloud Pak for Data control plane beneficial?

A. It ensures all projects are untethered for greater flexibility
B. Enhances project isolation while enabling resource access control
C. Disallows resource monitoring and management
D. It prevents any form of project organization

Answer: B

NEW QUESTION # 182
How do Massively Parallel Processing (MPP) and Symmetric Multiprocessing (SMP) differ in a Db2 environment?

A. MPP divides tasks among multiple processors, while SMP uses a single processor
B. MPP requires a shared memory architecture, whereas SMP does not
C. MPP is less suited for complex analytical tasks compared to SMP
D. SMP is more scalable than MPP

Answer: A

NEW QUESTION # 183
......

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