QREP Exam Questions & Answers

To run Analytics under Qlik Enterprise Manager, it is required to have a PostgreSQL Database installed. This is because the Analytics data for Qlik Enterprise Manager is stored in a PostgreSQL database. Before using the Analytics feature, you must ensure that PostgreSQL (version 12.16 or later) is installed either on the Enterprise Manager machine or on a machine that is accessible from Enterprise Manager1.

Here are the steps and prerequisites for setting up Analytics in Qlik Enterprise Manager:

Install PostgreSQL: The setup file for PostgreSQL is included with Enterprise Manager, and it must be installed to store the Analytics data1.

Create a dedicated database and user: A dedicated database and user in PostgreSQL should be created, which will own the tables accessed by the Enterprise Manager Analytics module1.

Configure connectivity: Connectivity to the PostgreSQL repository must be configured as described in the Repository connection settings1.

Data collection and purging: Configure data collection and purging settings as described in the Analytics - Data collection and purge settings1.

Register a license: A Replication Analytics license is required to use Analytics. If you have a license, you can register it by following the procedure described in Registering a license1.

The other options provided, such as Qlik Replicate (A), Qlik Compose (B), and both Qlik Compose and Replicate (D), are not components that must be installed to run Analytics under Enterprise Manager. The essential component is the PostgreSQL Database , which serves as the backend for storing the Analytics data1.

Therefore, the verified answer is C. PostgreSQL Database, as it is the required component to run Analytics under Qlik Enterprise Manager1.

Questions no: 38 Verified Answer: = B. Admin

Explanation: Step by Step Comprehensive and Detailed Explanation with all Reference: = In Qlik Replicate, different user roles are assigned specific permissions that dictate what tasks they can perform within the system. To import tasks into Qlik Replicate, a user must have the Admin role. Here's the breakdown of permissions for each role related to task management:

Admin: This role has the highest level of permissions, including the ability to import tasks. Users with the Admin role can perform all operations within Qlik Replicate, such as creating, designing, deleting, exporting, and importing tasks1.

Designer: Users with this role can create and design tasks but do not have permission to import tasks.

Operator: This role allows users to perform runtime operations like start, stop, or reload targets but does not include permissions to import tasks.

Viewer: Users with the Viewer role can view task history and other details but cannot perform task management operations like importing tasks.

Therefore, the correct answer is B. Admin, as only users with the Admin role are granted the permission to import tasks into Qlik Replicate1.

To batch-load a source automatically on a daily basis in Qlik Replicate, you would typically use a server scheduler. Here's how it can be done:

Set trigger through server scheduler (A): You can configure a scheduler on the server where Qlik Replicate is running to trigger the batch load process at a specified time each day. This could be done using the operating system's built-in task scheduler, such as Windows Task Scheduler or cron jobs on Linux systems1.

The scheduler would execute a command or script that starts the Qlik Replicate task configured for batch loading. The command would utilize Qlik Replicate's command-line interface or API to initiate the task1.

This approach allows for precise control over the timing of the batch load and can be adjusted to meet the specific scheduling requirements of the data replication process1.

The other options provided are not typically used for setting up an automatic daily batch load:

B . Set trigger through Advanced Run options: While Advanced Run options provide various ways to run tasks, they do not include a scheduling function for daily automation.

C . Set trigger through Task Designer: Task Designer is used for designing and configuring tasks, not for scheduling them.

D . Enable task on full load and apply changes: This option would start the task immediately and is not related to scheduling the task on a daily basis.

Therefore, the verified answer is A. Set trigger through server scheduler, as it is the method that allows for the automation of batch loading on a daily schedule1.

For replicating columns that contain large PDFs, the appropriate data type to use in Qlik Replicate is:

D . BLOB: This stands for Binary Large Object and is the data type used for storing large binary data such as PDF files. The BLOB data type is suitable for handling the size and binary nature of PDF files1.

The other options are not suitable for the following reasons:

A . DLOB: This is not a recognized data type in Qlik Replicate.

B . NCLOB: NCLOB, or National Character Large Object, is used for storing large text data in the national character set and is not optimal for binary data like PDFs.

C . NVARCHAR(1000): NVARCHAR is a character data type with a specified length, which would not be suitable for large binary objects like PDFs due to size limitations and the nature of the data.

For more information on data types and their usage in Qlik Replicate, you can refer to the official Qlik Replicate documentation on Replicate data types.

Questions no: 17 Verified Answer: = A. IBM IMS & E. HP NonStop

Explanation: Step by Step Comprehensive and Detailed Explanation with all Reference: = ARC (Attunity Replicate Connect) CDC agents are used for capturing changes (CDC) and can be utilized with both relational and non-relational endpoints supported by ARC. The endpoints that have ARC CDC agents include:

IBM IMS (A): This is a database and transaction management system, and it is listed as one of the endpoints supported by ARC CDC agents1.

HP NonStop (E): This is a platform for high-availability servers and is also supported by ARC CDC agents1.

The other options provided do not align with the endpoints that have ARC CDC agents:

B . IBMDB2Z/OS: While DB2 for z/OS is a common database system, it is not mentioned in the context of ARC CDC agents.

C . Kafka Source: Kafka is a streaming platform, and while it can be an endpoint for data, it is not listed as having ARC CDC agents.

D . SAPHANA: SAP HANA is an in-memory database, and it is not specified as having ARC CDC agents.

Therefore, the verified answers are A. IBM IMS and E. HP NonStop, as they are the endpoints that utilize ARC CDC agents for capturing changes1.