Qlik QREP Exam With Confidence Using Practice Dumps

When the connection to the source endpoint is unavailable for an extended period, and the log files are limited to only 2 hours of data before being deleted, the safest way to ensure a consistent state in the target endpoint is to use theReload Target Run option (A). This approach is recommended because it allows for a complete refresh of the target data, ensuring that it is in sync with the source once the connection is re-established.

TheReload Target Run optionis designed to handle situations where the replication logs are not sufficient to recover the replicated state due to extended outages or log retention policies. Byreloading the target, you can be confident that the data reflects the current state of the source, without relying on potentially incomplete change logs.

Starting processing from a fixed date and time (B) or recovering from a locally stored checkpoint © would not be reliable if the logs do not cover the entire period of the outage. Resuming the task and ignoring warnings (D) could lead to inconsistencies due to missed changes.

Therefore, theReload Target Run optionis the safest method to create a consistent state in the target endpoint under these circumstances1.

Qlik Replicate supports a variety of task types to accommodate different data replication needs. The three task types supported are:

LogStream to Staging Folder (A): This task type allows Qlik Replicate to save data changes from the source database transaction log to a staging folder.These changes can then be applied to multiple targets1.

Full load, apply, and store change (E): This is a comprehensive task type that includes a full load of the source database, applying changes to the target, and storing changes in an audit table on the target side1.

LogStream full load (F): Similar to the LogStream to Staging Folder, this task type involves saving data changes from the source database transaction log.However, it also includes a full load of the data to the target database1.

The other options provided do not align with the task types supported by Qlik Replicate:

B. Store changes bidirectional: While Qlik Replicate supports bidirectional tasks, the option as stated does not accurately describe a supported task type.

C. LogStream store changes: This option is not clearly defined as a supported task type in the documentation.

D. Scheduled full loads: Although Qlik Replicate can perform full loads, “Scheduled full loads” as a specific task type is not mentioned in the documentation.

Therefore, the verified answers areA,E, andF, as they represent the task types that Qlik Replicate supports according to the official documentation1.

To run daily reports about the changes that have occurred within the past 24 hours using Qlik Replicate, the option that must be set isStore Changes. This feature enables Qlik Replicate to keep a record of the changes that have occurred over a specified period, which in this case is the past 24 hours.

B. Store Changes: This setting allows Qlik Replicate to capture and store the changes made to the data in the source system.These stored changes can then be used to generate reports that reflect the data modifications within the desired timeframe1.

The other options are not specifically designed for the purpose of running daily change reports:

A. Apply Changes: This option is related to applying the captured changes to the target system, which is a different stage of the replication process.

C. Stage Changes: Staging changes involves temporarily storing the changes before they are applied to the target, which is not the same as storing changes for reporting purposes.

D. Full Load: The Full Load option is used to replicate the entire dataset from the source to the target, which is not necessary for generating reports based on changes within a specific timeframe.

For more information on how to configure the Store Changes option and generate reports based on the stored changes, you can refer to the official Qlik documentation and community discussions that provide insights into best practices for setting up replication tasks and managing change data2.