IBM A1000-003 Practice Exam 2025: Latest Questions

An organization is deploying IBM Cloud Pak for Data on Red Hat OpenShift and wants a single, consistent access point for users to launch services and manage workloads. Which Cloud Pak for Data component provides this common entry experience?

A data steward needs to ensure business terms and data assets have clear definitions and relationships, and that users can search for governed assets across the platform. Which capability should be used?

A team wants to build a machine learning model collaboratively using notebooks and visual tools, then track experiments within a project. Which service in Cloud Pak for Data best fits this need?

During an assessment, a client asks what should be confirmed before enabling a new Cloud Pak for Data service on OpenShift. Which prerequisite is most critical to validate first?

A customer requires strict network separation so that platform services run in one OpenShift namespace while project workspaces and user workloads run in separate namespaces. Which architectural approach best aligns with this requirement in Cloud Pak for Data?

A data governance team wants to prevent sensitive columns (for example, national identifiers) from being exposed to most analysts while still allowing datasets to be discoverable in the catalog. Which combination best addresses this requirement?

A model is trained in a Cloud Pak for Data project and must be deployed so applications can call it for real-time predictions with consistent scoring behavior. Which service is primarily used to deploy and host the model as an endpoint?

A client reports that analysts can see catalog assets but cannot open them in a project due to permission errors. What is the most likely cause?

An enterprise must support disaster recovery for Cloud Pak for Data by ensuring that persistent data and critical platform state can be restored after a cluster failure. Which approach is most appropriate?

A regulated organization wants to ensure that every model deployed for production scoring includes documentation, approval evidence, and the ability to trace which data and code produced the model. Which practice best satisfies this requirement in Cloud Pak for Data?

An organization is planning an IBM Cloud Pak for Data deployment on Red Hat OpenShift. The platform team asks what component provides common platform capabilities such as identity integration, metering, and licensing services for Cloud Pak workloads. Which component should be installed/configured?

A data steward wants to ensure analysts can quickly find trusted data assets, understand their definitions, and see business terms consistently applied across projects. Which capability best addresses this requirement?

A project team wants to create repeatable data science workflows where code, data preparation, model training, and evaluation steps are orchestrated and can be re-run consistently. Which service/capability should they use?

A company needs to enforce that personally identifiable information (PII) is masked for most users but visible to a small compliance group. They also want this policy to apply consistently across multiple analytic tools. What is the recommended approach?

A team deploys Cloud Pak for Data on OpenShift and notices that several services remain in a Pending state due to unbound PersistentVolumeClaims (PVCs). What is the most likely root cause?

An enterprise requires that data lineage is captured from ingestion through transformations and into analytics outputs to support audits and impact analysis. Which capability best supports this requirement?

A data engineering team must ingest data from multiple relational databases with minimal custom code and schedule incremental loads into an analytics environment. Which approach is most appropriate?

A team wants to deploy an ML model and ensure consistent runtime dependencies from development to production, while enabling scalable, API-based inference. Which deployment approach best meets the requirement?

A regulated client requires strong tenant isolation between two business units sharing the same OpenShift cluster hosting Cloud Pak for Data. They want to minimize the risk of accidental cross-access to data, secrets, and workloads. Which design is the best practice?

After implementing governance, a team finds that sensitive columns are still visible in downstream derived datasets created by users, even though the original source asset has masking rules. What is the most likely gap to investigate first?

A project team wants to standardize how business terms (for example, “Customer,” “Active Account”) are defined and reused across multiple analytics projects in Cloud Pak for Data. Which capability should they use to manage these definitions and link them to data assets?

An architect is designing a Cloud Pak for Data deployment on OpenShift and wants to reduce contention among multiple services (for example, governance and analytics) by ensuring predictable CPU and memory consumption. What is the most appropriate approach?

A data engineer can connect to a remote database from Cloud Pak for Data and see tables in a catalog, but attempts to run a Data Refinery flow fail with permission errors when reading the data. What is the most likely cause?

A data science team must deploy a model so that online applications can request predictions, and they also need to keep track of which model version produced each prediction for audit purposes. Which approach best meets these requirements in Cloud Pak for Data?

During solution assessment, a customer requires that sensitive columns (for example, national IDs) be protected so that most users can analyze datasets but cannot see raw values, while a small group can view full details. Which design best satisfies this requirement in Cloud Pak for Data?