IBM C1000-173 Exam Dumps

Within IBM Knowledge Catalog as part of IBM Cloud Pak for Data, governing data lakes is enabled via integration with Data Virtualization. This approach supports automated data discovery, cataloging, tagging, and virtualization, allowing users to access enterprise data virtually---without physical movement. Policies and governance metadata are applied automatically to virtualized assets, enabling secure and efficient data consumption. Manual processes are not required for discovery, and data is masked selectively based on policies---not completely masked without user intervention. Thus automation and virtualization are central, making statement B correct.

For Cloud Pak for Data deployed on a FIPS-enabled cluster, the supported method for backup and restore is the online backup and restore to the same cluster. This method ensures that the data and configuration remain compliant with FIPS encryption standards. Offline and cross-cluster restore methods are not supported under FIPS constraints due to strict requirements around key handling and encryption. The Snap and Restore Tool and Watson Backup Assistant are not applicable to this context.

To set up IBM Data Replication in Cloud Pak for Data, administrators must follow a sequence that begins with defining the source (such as a transactional database), then defining the target system (such as a data lake or warehouse), and finally configuring the replication process. This setup allows for near real-time data synchronization. User definitions, server setup, and data management rules are involved elsewhere in the platform but are not the essential steps for replication configuration.

Watson OpenScale includes advanced monitoring capabilities for deployed AI models, including drift detection. Data drift refers to changes in input data distributions over time, which can degrade model performance. OpenScale continuously compares incoming data to the original training data to detect deviations and alert users when retraining may be required. It does not manage storage, data overwrites, or rule-based systems, making option B the only correct choice.

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.