Qlik QREP Dumps - Pass Qlik Replicate Certification Exam in First Attempt 2026

After a Qlik Replicate administrator creates a new task, runs a Full Load test, and turns on Change Processing, the method to test this task would be to:

Stop the task: This ensures that no active processes are running that could interfere with the testing.

Run -> Advanced Run Options: This step allows the administrator to access more specific settings that can control how the task is executed.

Start Change Processing Only: This option will start the Change Data Capture (CDC) phase without re-running the Full Load. It's used to test the CDC mechanism specifically, ensuring that changes made at the source are captured and applied to the target correctly.

This method is supported by best practices in the Qlik community and documentation, which suggest using the Advanced Run Options to control the task's behavior for testing purposes1. It allows the administrator to verify that the Change Processing is set up correctly and is functioning as expected without the need to reload the target or recreate the task entirely. This approach is efficient and effective for testing the CDC functionality in isolation.

When a Qlik Replicate administrator needs to access data from a CRM application, the most efficient and direct method is often through the application's REST API. Here's why:

Connect to the REST API provided by the application : Many modern CRM applications provide a REST API for programmatic access to their data. This method is typically supported by data integration tools like Qlik Replicate and allows for a more seamless and real-time data extraction process. The REST API can provide a direct and efficient way to access the required data without the need for intermediate steps1.

Connect directly to the application (A): While this option might seem straightforward, it is not always possible or recommended due to potential limitations in direct application connections or the lack of a suitable interface for data extraction.

Export tables to CSVs in a shared folder and connect to that (B): This method involves additional steps and can be less efficient. It requires manual intervention to export the data and does not support real-time data access.

Connect to the underlying RDBMS (D): Accessing the underlying relational database management system (RDBMS) can be an option, but it may bypass the business logic implemented in the CRM application and could lead to incomplete or inconsistent data extraction.

Given these considerations, the REST API method is generally the preferred approach for accessing CRM application data in a structured and programmable manner, which aligns with the capabilities of Qlik Replicate213.

To identify the internal commands that Qlik Replicate is executing prior to an error, the Trace logging level should be used. This level provides detailed information about the operations being performed by Qlik Replicate, including the internal commands executed before an error occurs1.

Here's how the Trace logging level works in Qlik Replicate:

When logging is set to Trace, the log lines are identified with ]T:. This indicates that the log will include detailed trace information about the internal workings of Qlik Replicate, such as sending control records to components or waiting for termination of threads1.

The Trace level is more detailed than Warnings (]W:) and Errors (]E:), which only show warning and error messages without the detailed context of the operations leading up to them1.

The Trace level is also distinct from Verbose (]V:), which provides even more detailed logging information but may not be necessary for identifying the commands leading up to an error1.

Therefore, the correct answer is C. Trace, as it is the appropriate logging level to use when you need to analyze the actions performed by Qlik Replicate just before an error occurs1.

In Qlik Replicate, when multiple schema rename rules are applied, the final schema name is determined by the last applied setting that affects the schema name directly. Here's how the process works:

Global Transformation to rename schema to 'USER1': This rule will initially rename the schema from 'HR' to 'USER1'. However, this is not the final schema name as further changes are applied later in the task settings1.

Task Settings -> Target Metadata to enter the Target table schema as 'USER2': This setting overrides the previous global transformation rule and sets the target schema name to 'USER2'. This is because the Target Metadata settings are applied after the Global Transformations and directly affect the target schema name1.

Global Transformation to add a new column named 'SCHEMA' with expression as 'USER3': While this rule adds a new column with a value of 'USER3', it does not change the schema name itself. It only affects the content of a column within the tables1.

Therefore, the final target schema name, after considering all the applied settings, is D. USER2. This is because the Target Metadata setting in the task settings has the final say on the target schema name, and it is set to 'USER2'1.

For stream endpoint types like Kafka or Azure Event Hubs in Qlik Replicate, there are specific limitations that apply to the replication options and target table preparation options:

D . The Store Changes replication option is not supported: This limitation is explicitly mentioned for Kafka1 and Azure Event Hubs23. The Store Changes mode is not supported when using these stream endpoints, meaning that changes cannot be stored for later retrieval or reporting.