Oracle Oracle Cloud Database 2023 Migration and Integration Professional 1z0-1094-23 Exam Dumps: Updated Questions & Answers (October 2025)

Oracle Data Pump can move data to the cloud using methods such as importing over a database link or importing a dump file from Oracle Cloud Infrastructure (OCI) Object Storage. Importing over a database link allows for direct data transfer between databases, while importing from OCI Object Storage enables the use of dump files stored in the cloud, facilitating flexible and efficient cloud migrations.

To pause a ZDM job, you can use the -pauseafter option with the zdmcli migrate database command to specify a migration phase where the process should be paused. Alternatively, the zdmcli suspend job command with the job ID can pause the migration at any point, providing flexibility in managing the migration process.

In Oracle Data Integrator (ODI) Change Data Capture (CDC) processes, the JV$D view and J$ table are critical components for monitoring changed data capture activities. The JV$D view provides information about the CDC subscriber view definitions, while the J$ table stores the actual changed data records. Inspecting these database objects can help debug and verify that the CDC process is correctly capturing and writing changed data.

Data Pump can utilize Dumpfile for unloading and loading data, where data is exported to and imported from binary dump files. Network mode allows Data Pump to transfer data directly between databases using database links, without the need for intermediate dump files, facilitating efficient data migrations and consolidations.

Oracle GoldenGate is the preferred integration product for real-time data replication between Oracle Databases. It provides low-impact, real-time change data capture, transformation, and delivery, enabling high availability solutions, real-time data integration, transactional change data capture, data replication, transformations, and verification between operational and analytical enterprise systems.

Oracle Data Integrator (ODI) supports the integration of heterogeneous data sources, including databases and flat files, within a single mapping. This capability allows for the joining of data from different source types, such as an Oracle database table and a flat file, and loading the combined data into a target database like DB2. ODI's flexible architecture and support for various technologies enable this seamless integration, facilitating complex data transformation and loading tasks across diverse data environments.

Oracle Data Guard is the method that provides the least downtime for database migration. It ensures high availability, data protection, and disaster recovery for Oracle databases. By maintaining a synchronized standby database, Data Guard enables seamless role transitions and minimal downtime during planned maintenance, making it an optimal choice for migrations requiring continuous availability.

Installing Oracle Zero Downtime Migration (ZDM) software requires a system with at least 8 GB of RAM to ensure adequate performance. Additionally, specific Linux packages, including "glibc-devel" and "expect," must be installed to satisfy dependencies that ZDM components might have, ensuring a successful installation and operation of the ZDM service host.

In Oracle Data Integrator (ODI) for data warehouse loads, the "Consistent" journalizing type should be used to ensure referential integrity is maintained between related tables, such as order header and order line items tables. This journalizing type captures changes in a consistent manner across multiple tables, ensuring that the data loaded into the target maintains the integrity and relationships defined in the source data model.

ELT (Extract, Load, Transform) offers benefits over traditional ETL (Extract, Transform, Load) by reducing network traffic and eliminating the need for dedicated transformation servers. In ELT, data transformation occurs within the target database leveraging its native processing capabilities, which can lead to more efficient use of resources and better performance, especially with large data volumes and complex transformations.