C1000-173 Exam Dumps - IBM Data and AI: Data and AI Questions and Answers

watsonx.data uses Apache Iceberg tables as the open table format for data sharing across platforms like Db2 Warehouse, Netezza, and other compatible data management solutions. Iceberg provides a transactional and schema-evolution-friendly table layer, allowing multiple engines to read and write data concurrently. This approach avoids proprietary loaders or simple file transfers and ensures efficient interoperability between different systems.

In IBM Data Virtualization, caches must be manually defined by administrators. While monitoring and query performance statistics can guide where caching would be beneficial, the creation and configuration of caches (e.g., refresh schedules and scope) are manual tasks. There is no automated cache creation mechanism (A), nor are DataStage flows used for cache maintenance (B). Suggestions based on statistics (D) may assist administrators, but they do not automatically create the caches.

The Data Engineer role in IBM Cloud Pak for Data includes permissions necessary for managing the data pipeline lifecycle. This includes the ability to create projects, manage data assets, and configure data protection rules, which are critical for ensuring data privacy and governance. The role does not include platform-level administrative privileges like managing the platform or monitoring all workloads. Workflow management is typically assigned to users with broader project or orchestrator roles.

Watson Assistant integrates with telephone systems through the Voice Gateway service. Voice Gateway captures real-time telephone voice interactions and can route them to a Watson Assistant chatbot or forward them for transcription and analytics. It enables cognitive agents to interact over voice channels and supports integration with SIP-based telephony systems. Voice Agent, Analyzer, and Transcriber are not standard Watson Assistant components within Cloud Pak for Data.

"You can create a maximum of10instances per deployment. After you reach the maximum number, the New instance button is not displayed in IBM Cloud Pak for Data."

Watson OpenScale focuses on the monitoring and governance of AI models. Its API allows users to programmatically measure model outcomes, track metrics like accuracy, precision, fairness, and drift, and support compliance with responsible AI practices. It does not build chat interfaces (A), manage data in Watson Studio (B), or extract answers from documents (C). These capabilities are aligned with other Watson services, but OpenScale is centered on AI governance and model performance measurement.

Data masking in IBM Cloud Pak for Data is primarily supported by IBM Knowledge Catalog and Data Privacy services. IBM Knowledge Catalog enforces masking through Data Protection Rules, which dynamically mask sensitive fields when data is accessed through virtualized connections. Data Privacy allows creating masking flows and rules that transform datasets while maintaining usability for analytics, ensuring sensitive data is hidden or obfuscated. DataStage and Db2 Data Gate are ETL and data replication tools, respectively, and SPSS is an analytics tool, none of which natively implement comprehensive masking as a core capability.

watsonx.data is an open hybrid data lakehouse platform, combining the strengths of a data lake (flexibility and cost efficiency for unstructured data) with the structured query and performance features of a data warehouse. It is designed to handle both analytics and large-scale data storage, making it a hybrid solution rather than exclusively a data lake or data warehouse.