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IBM C1000-173 Exam Syllabus Topics:

Topic	Details
Topic 1	Architect with Analytic Services: This domain targets a Data Analytics Architect and focuses on designing solutions using analytic components of Cloud Pak for Data. Architecting with DataStage involves creating data integration and ETL pipelines. Data Refinery architectures prepare and cleanse data for analysis. Db2 Big SQL solutions address querying large distributed data sets with SQL, facilitating analytics across diverse data sources.
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	Architect with AI Series: This section measures the skills of an AI Solution Architect and includes designing architectures for solutions involving various IBM Watson AI services. Architecting with Watson Assistant involves creating conversational AI interfaces. Watson Discovery solutions focus on building cognitive search and content analytics applications. Watson Pipelines solutions involve orchestrating data science workflows. Watson OpenScale architectures enable AI model monitoring and governance. Architecting with Match 360 supports personalized engagement by integrating multi-channel customer insights.
Topic 5	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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q58-Q63):

NEW QUESTION # 58
A customer wants to manage Cloud Pak for Data secrets via an existing supported vault system. What is needed to integrate any supported vault systems into Cloud Pak for Data?

A. Client key in .key or .pem format to authenticate to the vault.
B. Fully qualified URL of the vault.
C. Username and password of the vault.
D. Client certificate to authenticate to the vault.

Answer: B

Explanation:
To integrate a supported vault system withIBM Cloud Pak for Data, thefully qualified URLof the external vault is a required component for establishing communication between Cloud Pak for Data and the vault. This is typically configured in theexternal secrets managersettings.
While authentication credentials (like client certificates or keys) are also necessarydepending on the authentication method used, thefully qualified URLis universally required to locate and connect to the vault.
IBM Cloud Pak for Data supports integration with vaults such as:
* HashiCorp Vault
* AWS Secrets Manager
* Azure Key Vault
* IBM Key Protect
For more details, refer to:
IBM Cloud Pak for Data: Using external secrets managers

NEW QUESTION # 59
Which two of the following can be used with Watson Pipelines?

A. PowerShell
B. Notebooks
C. Postgres
D. Bash scripts
E. Db2 Big SQL

Answer: B,D

Explanation:
Watson Pipelines in Cloud Pak for Data support orchestration of diverse workload types including notebooks (Python or similar interactive environments) and scripts such as Bash. These pipeline components allow integration of notebook cells or shell scripts as tasks. There is no built#in support for executing PowerShell tasks directly (unless wrapped in Bash-like containers), and Postgres is used as a data source-not a pipeline component type. While Db2 Big SQL can be invoked within a notebook or script, it is not itself a pipeline component. Therefore the supported types in pipelines are notebooks and Bash scripts.

NEW QUESTION # 60
Which features of the IBM Knowledge Catalog service are unavailable with the Data Governance Express offering?

A. Advanced metadata export and lineage
B. Semantic search and metadata analysis
C. Data quality features in analytics projects and ETL
D. Lineage and semantic search

Answer: A

Explanation:
IBM Knowledge Catalog's Data Governance Express offering is a lightweight configuration meant for streamlined governance needs. It includes core capabilities like cataloging and basic lineage but does not support advanced metadata export or full-scale lineage visualization and tracking features. These advanced features are only available in the full IBM Knowledge Catalog service.
The Express tier is designed for simpler use cases and quicker onboarding with limited governance overhead.

NEW QUESTION # 61
In the context of Db2 services, which two authentication methods ensure secure API access?

A. Unencrypted credentials
B. API keys
C. Basic authentication
D. OAuth 2.0

Answer: C,D

NEW QUESTION # 62
What are two ways to customize Knowledge Accelerators to meet specific requirements?

A. Change Knowledge Accelerator content inline.
B. Customize the content in a separate namespace.
C. Place Knowledge Accelerator content in a "development" vocabulary separate from the main stream "enterprise vocabulary".
D. Create a separate project for any customized content.
E. Use a GitHub Repo to manage any changes.

Answer: C,D

Explanation:
Customization of Knowledge Accelerators in IBM Cloud Pak for Data is a structured process to preserve the integrity of base content while allowing for extension. The recommended approaches include:
Creating a separate project for customizations, so that changes are isolated and easily managed without affecting the source accelerator.
Using a "development" vocabulary where custom terms and structures are created. This is separate from the "enterprise vocabulary," which contains the unmodified, original Knowledge Accelerator content. Inline editing of the original content is discouraged. Use of GitHub or namespaces is not part of the official customization workflow.

NEW QUESTION # 63
......

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