QREP Qlik Replicate Certification Exam Questions and Answers

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.

For tasks involving Kafka as a target in Qlik Replicate, the valid options are:

A. Full Load and Apply Change: This combination is valid because Kafka can be used both for initial full loads of data and for applying changes captured through CDC (Change Data Capture).In a task with a Kafka target endpoint, each source record is transformed into a message which is then written to a partition in the specified topic1.

The other options are not typically used with Kafka in Qlik Replicate:

B. Full Load and Stage Change: Staging changes is not a standard task option when using Kafka as a target.

C. Apply Change and Store Change: While Kafka can be used to apply changes, the “Store Change” option is not a recognized task option for Kafka targets.

D. Full Load and Store Change: Similarly, “Store Change” is not a standard task option for Kafka targets.

For more information on how to set up and use Kafka as a target endpoint in Qlik Replicate, including the configuration of Full Load and Apply Change tasks, you can refer to the official Qlik community articles and support resources21.

Theattrep_apply_exceptionstable in Qlik Replicate is used for troubleshooting specific issues that occur during the data replication process. Based on the documentation and community discussions, the two situations where this table can be particularly useful are:

Apply conflicts (B): This table records errors related to conflicts that occur when applying changes to the target system.For instance, if there is a primary key violation or a constraint failure, the details of the conflict are logged in this table1.

Data errors (E): The table also captures errors related to the data itself, such as missing data or data type mismatches.If a record cannot be applied due to data-related issues, the error message and the statement that caused the error are stored in theattrep_apply_exceptionstable2.

Theattrep_apply_exceptionstable is not typically used forabnormal termination (A),table errors ©, orenvironment errors (D)as these issues are generally logged elsewhere within the system or require different troubleshooting approaches. For example, abnormalterminations might be logged in system event logs, while environment errors could be related to infrastructure issues outside the scope of Qlik Replicate’s control tables.

To set all incoming columns to match a single schema in Qlik Replicate, an administrator should use theGlobal Transformationsfeature. Here’s the process:

Navigate to theGlobal Transformationssection within the Qlik Replicate task settings.

Within Global Transformations, there is an option to define transformations that apply to all tables and columns being replicated.

Use theSchemaoption within Global Transformations to specify the target schema for all incoming columns.

This approach ensures that all incoming data conforms to a predefined schema, which is particularly useful when consolidating data from multiple sources into a single target schema.It allows for the standardization of column names, data types, and other schema-related attributes across all tables involved in the replication task12.

The other options provided do not directly address the requirement to set all incoming columns to match a single schema:

A. Table Selection - Schema: This option is more about selecting which tables and schemas to include in the replication task, rather than defining a global schema for all columns.

B. Global Transformations - Add FilterandC. Add Filter - Schema: While filters are used to specify conditions for data transformation or selection, they do not provide a means to globally set the schema for all incoming columns.

Therefore, the verified answer isD. Global Transformations - Schema, as it is the correct method to set all incoming columns to match a single schema in Qlik Replicate12.

Questions no:38Verified Answer: = B. AdminStep by Step Comprehensive and Detailed Explanation with all References: =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 theAdminrole. 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 isB. Admin, as only users with the Admin role are granted the permission to import tasks into Qlik Replicate1.

In Qlik Enterprise Manager, permissions can be managed in a granular way, and one of the key features is the ability to inherit permissions. Here’s how it works:

Inherited permissions for all functions ©: By default, inheritance is enabled for all objects, including users and groups.This means that permissions are automatically carried over from the parent object, ensuring consistency and ease of management across different levels of the organizational structure1.

Using the same permissions as in Qlik Replicate (A)andUsing the same permissions as in Qlik Replicate and Qlik Compose (D): While Qlik Enterprise Manager may integrate with Qlik Replicate and Qlik Compose, the permissions are not directly transferred or used in the same way. Each tool has its own set of permissions and roles that need to be configured separately.

Transfer rights from Qlik Replicate (B): There is no direct option to transfer rights from Qlik Replicate to Qlik Enterprise Manager. Permissions need to be set within the Enterprise Manager itself, although it may be guided by the roles and permissions defined in Qlik Replicate.

Therefore, the verified answer isC. Inherited permissions for all functions, as it reflects the capability of Qlik Enterprise Manager to set permissions based on inheritance, which simplifies the management of user permissions across the system1.

When merging databases, especially of such large sizes (12 TB and 15 TB), it is crucial to ensure data integrity and consistency. The recommended approach is to:

Stop the Replication Task: This is important to prevent any changes from being replicated to the target while the IBM load process is ongoing.

Perform the IBM Load: Execute the IBM load to merge the database into the existing database.

Resume the Replication Task: Once the IBM load has been successfully completed, the replication task can be resumed.

This approach ensures that the data loaded via IBM load is not missed or duplicated in the target database. It also allows Qlik Replicate to continue capturing changes from the point where the task was stopped, thus maintaining the continuity of the replication process.

It’s important to note that creating a new task after the IBM load (Option D) could lead to complexities in managing the data consistency and might require additional configuration. Continuing to run the task (Option C) could result in conflicts or data integrity issues during the load process. Therefore, Option B is the safest and most reliable approach to ensure a smooth merge of the databases.

For further details and best practices, you can refer to the official Qlik Replicate documentation and support articles which provide guidance on similar scenarios1234.

For Qlik Replicate’s Change Data Capture (CDC) process, the valid source endpoint types include:

A. Classic Relational RDBMS: These are traditional relational database management systems that support CDC.Qlik Replicate can capture changes from these systems using log-based CDC tools which are integrated to work with most ETL tools1.

C. SAP ECC and Extractors: SAP ECC (ERP Central Component) and its extractors are also supported as source endpoints for CDC in Qlik Replicate.This allows for the replication of data changes from SAP’s complex data structures1.

The other options provided are not typically associated with CDC in Qlik Replicate:

B. MS Dynamics direct access: While Qlik Replicate can connect to various data sources, MS Dynamics is not commonly listed as a direct source for CDC.

D. Generic REST APIs Data Lake file formats: REST APIs and Data Lake file formats are not standard sources for CDC as they do not maintain transaction logs, which are essential for CDC to track changes.

For detailed information on setting up source endpoints and enabling CDC, you can refer to the official Qlik documentation and community articles that discuss the prerequisites and configurations needed for various source endpoints2345.

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 onReplicate data types.

The server logs in Qlik Replicate provide information about the Qlik Replicate Server instance, rather than individual tasks.The logs can include various levels of information, such as errors, warnings, info, trace, and verbose details1. Specifically, the server logs can provide insights into:

Network and performance issues: These might be indicated by error or warning messages related to connectivity or performance bottlenecks.

Load status and performance of task: While the server logs focus on the server instance, they may contain information about the overall load status and performance, especially if there are server-level issues affecting tasks.

Specific task information: The server logs can include information about tasks, particularly if there are errors or warnings that pertain to task execution at the server level.

Qlik Replicate Server status: This includes general information about the server’s health, status, and any significant events that affect the server’s operation.

Therefore, while the server logs can potentially contain a range of information, the primary purpose is to provide details on theQlik Replicate Server status(D), including any issues that may impact the server’s ability to function properly and manage tasks231.

When loading data into a Cloud Storage Data Warehouse like Snowflake, Synapse, Redshift, or Big Query, the type of storage required for the COPY statement isObject Storagesuch as Azure Data Lake Storage (ADLS), Amazon S3, or Google Cloud Storage (GCS). This is because these cloud data warehouses are designed to directly interact with object storage services, which are scalable, secure, and optimized for large amounts of data.

For example, when using Microsoft Azure Synapse Analytics as a target endpoint in Qlik Replicate, the COPY statement load method requires the Synapse identity to be granted “Storage Blob Data Contributor” permission on the storage account, which is applicable when using either Blob storage or ADLS Gen2 storage1.Similarly, for Amazon S3, the Cloud Storage connector in Qlik Application Automation supports operations with files stored in S3 buckets2.The prerequisites for using Azure Data Lake Storage (ADLS) Gen2 file system or Blob storage location also indicate the necessity of these being accessible from the Qlik Replicate machine3.

Therefore, the correct answer isD. Object Storage (ADLS, S3, GCS), as these services provide the necessary infrastructure for the COPY statement to load data efficiently into cloud-based data warehouses.

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

When a new column is added to one of the tables in a Qlik Replicate task, the administrator should stop and then resume the task to replicate this change. This process allows Qlik Replicate to recognize the structural change and apply it accordingly.

The steps involved in this process are:

Stop the task: This ensures that no data changes are missed during the schema change.

Resume the task: Once the task is resumed, Qlik Replicate will pick up the DDL change and apply the new column to the target system.

This procedure is supported by the Qlik Replicate’s DDL handling policy, which can be set to perform an “alter target table” when the source table is altered.This means that when the task is resumed, the new columns from the source tables will be added to the Replicate target1.

It’s important to note that while stopping and resuming the task is generally the recommended approach, the exact steps may vary depending on the specific configuration and version of Qlik Replicate being used. Therefore, it’s always best to consult the latest official documentation or support resources to ensure the correct procedure for your environment.

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.

To run a Qlik Replicate Task at a high-performance level, the main hardware components that are recommended include:

Cores: A higher number of cores is beneficial for handling many tasks running in parallel and for prioritizing full-load performance1.

SSD (Solid State Drive): SSDs are recommended for optimal performance, especially when using a file-based target or dealing with long-running source transactions that may not fit into memory1.

Network bandwidth: Adequate network bandwidth is crucial to handle the data transfer requirements, with 1 Gbps for basic systems and 10 Gbps for larger systems being recommended1.

The other options do not encompass all the recommended hardware components for high-performance levels in Qlik Replicate tasks:

A. SSD, RAM: While these are important, they do not include the network bandwidth component.

B. Cores, RAM: This option omits the SSD, which is important for disk performance.

D. RAM, Network bandwidth: This option leaves out the cores, which are essential for processing power.

For detailed hardware recommendations for different scales of Qlik Replicate systems, you can refer to the official Qlik documentation onRecommended Hardware Configuration.