IBM C1000-173 Exam Dumps

IBM Knowledge Catalog is the core governance and cataloging service within Cloud Pak for Data that enables the delivery of trusted, business-ready data to AI and analytics pipelines. It provides data lineage, metadata management, access policies, and quality scores, ensuring data consumers use curated and compliant data. Watson Machine Learning and its accelerator are focused on model training and inference, while IBM Data Catalog is a former term replaced by Knowledge Catalog in recent versions.

Collaborators in IBM Knowledge Catalog are granted access to data assets that have been properly governed and made available through connections. Once a connection is established by an administrator or asset owner, users with collaborator roles can access the data without needing to re-enter credentials. This simplifies secure data consumption and aligns with enterprise access control policies. They do not see underlying credentials, and access is not limited to document types like PDFs.

Knowledge Accelerators are a part of IBM Knowledge Catalog in IBM Cloud Pak for Data and provide predefined industry-specific business terms and relationships. These accelerators are not included by default with sample assets nor automatically deployed through the Cloud Pak for Data marketplace. Instead, they are imported using dedicated API endpoints provided by IBM for Knowledge Accelerators. Deployment involves uploading the accelerator assets using the IBM Knowledge Accelerator API, and once imported, they can be customized and published within the governance framework. This approach provides the flexibility required for various enterprise governance models.

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.

To integrate a supported vault system with IBM Cloud Pak for Data, the fully qualified URL of the external vault is a required component for establishing communication between Cloud Pak for Data and the vault. This is typically configured in the external secrets manager settings.

While authentication credentials (like client certificates or keys) are also necessary depending on the authentication method used, the fully qualified URL is 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