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IBM C1000-173 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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 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 4	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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q179-Q184):

NEW QUESTION # 179
An architect is working with a team to configure Dynamic Workload Management for a single DataStage instance on Cloud Pak for Data. Auto-scaling has been disabled and the maximum concurrent jobs has been set to 5. What will happen if a sixth concurrent job is executed?

A. The sixth job will queue until one of the other concurrent jobs completes.
B. The sixth job will fail and will need to be restarted.
C. The sixth job will start if resources are available and will automatic.

Answer: A

Explanation:
Queueing mechanism is in place. Since the maximum concurrent jobs are limited to 5, the sixth job will not start immediately. Instead, it will queue and wait for one of the currently running jobs to complete, making room for the sixth job to execute.

NEW QUESTION # 180
Which statement describes MPP (Massively Parallel Processing) Database architecture?

A. A data warehouse that needs all compute nodes to access a shared data store simultaneously.
B. An analytics environment that improves performance by dividing the data across many nodes.
C. A transactional system which uses multiple nodes for maximum availability.
D. Two or more databases kept in sync via two-phase commit.

Answer: B

Explanation:
MPP, or Massively Parallel Processing, is a database architecture model where data is divided and processed across multiple compute nodes in parallel. Each node works independently on a portion of the data, dramatically improving query performance and throughput for analytics workloads. This model is ideal for big data and analytical queries, not transactional workloads. It differs from shared-disk models or replication strategies like two-phase commit. The correct definition involves distributed data and parallel query execution, as described in option C.

NEW QUESTION # 181
What outcomes can be achieved from Match 360?

A. Connect disparate data sources to provide a virtual view of your data.
B. Uses a dialog format to talk with your data to get insights.
C. Produces statistics and graphs to let users analyze and explore master data.
D. Produces a AI based dashboard to let users analyze business data.

Answer: C

Explanation:
Match 360 is IBM's master data management (MDM) service integrated into Cloud Pak for Data.
It produces master data views along with statistics, graphs, and insights that allow users to explore, analyze, and understand their master data entities (e.g., customers, products). While it does integrate data from disparate sources, its focus is on consolidating and providing master data analysis rather than virtual views (B) or conversational analytics (A).

NEW QUESTION # 182
What is a significant advantage of using Db2 services in a cloud environment?

A. Enhanced data security
B. Decreased processing speed
C. Reduced physical storage requirements
D. Limited data scalability

Answer: C

NEW QUESTION # 183
When planning to expose REST-based APIs for Db2, what is an essential consideration for the route configuration?

A. Dynamic route adjustment based on traffic
B. Static route assignment
C. Inconsistent route naming conventions
D. Route hardcoding within the application

Answer: A

NEW QUESTION # 184
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