Talend Talend Core Developer Practice Exams
Last updated on Oct 21,2026- Exam Code: Talend Core Developer
- Exam Name: Talend Core Certified Developer Exam
- Certification Provider: Talend
- Latest update: Oct 21,2026
Question #1
You created a Remote Engine in Talend Cloud and copied the Remote Engine key. You downloaded the Remote Engine script for your Linux system, and now you need to pair the engine manually.
Which options can you use to set the key? Choose 2 answers.
- A . In Studio Talend Cloud preferences.
- B . In the Remote Engine web service page.
- C . In the key configuration file of the engine.
- D . In the engine run script command line as a parameter.
Correct Answer: B, C
B, C
Explanation:
Comprehensive and Detailed
To manually pair a Remote Engine with Talend Cloud, you can set the pairing key using the following methods:
In the Remote Engine web service page (Option B):
Access the Remote Engine’s web interface, typically available at http://localhost:8043/configuration.
Enter the pairing key obtained from the Talend Management Console.
Click on PAIR REMOTE ENGINE to establish the connection.
In the key configuration file of the engine (Option C):
Locate the preauthorized.key.cfg file in the Remote Engine’s etc directory.
Open the file and paste the pairing key into the remote.engine.pre.authorized.key parameter.
Save the changes and restart the Remote Engine to apply the configuration.
Why not other options?
Option A: Setting the pairing key in Talend Studio’s preferences is not applicable for pairing a Remote Engine.
Option D: While it’s technically possible to pass the pairing key as a parameter in the engine’s run script, it’s not the standard or recommended method.
Reference: Talend Remote Engine User Guide
B, C
Explanation:
Comprehensive and Detailed
To manually pair a Remote Engine with Talend Cloud, you can set the pairing key using the following methods:
In the Remote Engine web service page (Option B):
Access the Remote Engine’s web interface, typically available at http://localhost:8043/configuration.
Enter the pairing key obtained from the Talend Management Console.
Click on PAIR REMOTE ENGINE to establish the connection.
In the key configuration file of the engine (Option C):
Locate the preauthorized.key.cfg file in the Remote Engine’s etc directory.
Open the file and paste the pairing key into the remote.engine.pre.authorized.key parameter.
Save the changes and restart the Remote Engine to apply the configuration.
Why not other options?
Option A: Setting the pairing key in Talend Studio’s preferences is not applicable for pairing a Remote Engine.
Option D: While it’s technically possible to pass the pairing key as a parameter in the engine’s run script, it’s not the standard or recommended method.
Reference: Talend Remote Engine User Guide
Question #2
You want to improve the Trust Score™ of your dataset as a dataset owner.
Which actions should you perform? Choose 2 answers.
- A . Improve the quality of the dataset using Pipeline Designer
- B . Change the dataset score manually
- C . Use the dataset in an ETL Job
- D . Add ratings to the dataset
Correct Answer: A, D
A, D
Explanation:
Comprehensive and Detailed
To enhance the Trust Score™ of a dataset:
Improve the quality of the dataset using Pipeline Designer (Option A):
Utilizing Talend’s Pipeline Designer allows you to cleanse, transform, and enrich your data, thereby improving its quality and, consequently, its Trust Score™.
Add ratings to the dataset (Option D):
Encouraging users to rate the dataset increases its popularity metric, positively impacting the overall Trust Score™.
Why not other options?
Option B: The Trust Score™ is automatically calculated based on specific metrics; it cannot be manually altered.
Option C: While using the dataset in ETL jobs indicates its utility, it does not directly influence the Trust Score™ unless it affects metrics like usage or popularity.
Reference: Talend Cloud Data Inventory User Guide
A, D
Explanation:
Comprehensive and Detailed
To enhance the Trust Score™ of a dataset:
Improve the quality of the dataset using Pipeline Designer (Option A):
Utilizing Talend’s Pipeline Designer allows you to cleanse, transform, and enrich your data, thereby improving its quality and, consequently, its Trust Score™.
Add ratings to the dataset (Option D):
Encouraging users to rate the dataset increases its popularity metric, positively impacting the overall Trust Score™.
Why not other options?
Option B: The Trust Score™ is automatically calculated based on specific metrics; it cannot be manually altered.
Option C: While using the dataset in ETL jobs indicates its utility, it does not directly influence the Trust Score™ unless it affects metrics like usage or popularity.
Reference: Talend Cloud Data Inventory User Guide
Question #3
Which capabilities does Traces Debug provide?
Choose 2 answers
- A . Filtering which data is propagated by a flow
- B . Advancing one column at a time
- C . Breaking on a selected line of code
- D . Breaking when an input column fulfills a condition
- E . Advancing one row at a time
Correct Answer: D, E
D, E
Explanation:
Trace Debug mode is a feature that allows you to trace each row processed by your job components and see the values of each column in each row. You can access this mode by opening the Debug Run tab of the Run view and clicking on Trace Debug button.
The capabilities that Trace Debug mode provides are:
Breaking when an input column fulfills a condition. You can set breakpoints on traces based on a condition or an expression that involves input data columns. For example, you can set a breakpoint to pause your job when a customer name contains a certain string or when a product price exceeds a certain value. To set a breakpoint based on a condition, you need to right-click on a trace on your job design workspace and select Show Breakpoint Setup option. This will open a dialog box where you can enter a condition or an expression for your breakpoint.
Advancing one row at a time. You can advance the execution of your job one row at a time by using the Step Over button in the toolbar of the Run view. This will allow you to see how each row is processed by your job components and how it affects the output data.
The capabilities that Trace Debug mode does not provide are:
Filtering which data is propagated by a flow. You cannot filter which data is propagated by a flow in Trace Debug mode. A flow is a link that shows the data transfer between components in your job design workspace. In Trace Debug mode, you can see the data flow on each trace and inspect the values of each column for each row processed by your job. However, you cannot change which rows are propagated by a flow based on a condition or an expression.
Advancing one column at a time. You cannot advance the execution of your job one column at a time in Trace Debug mode. You can only advance the execution of your job one row at a time by using the Step Over button in the toolbar of the Run view. This will allow you to see how each row is processed by your job components and how it affects the output data. However, you cannot see how each column is processed by your job components and how it affects the output data.
Breaking on a selected line of code. You cannot break on a selected line of code in Trace Debug mode. You can only break on a trace based on a condition or an expression that involves input data columns. To break on a selected line of code, you need to use Java Debug mode. Java Debug mode allows you to debug your job code in Java or Perl and see the values of each variable or expression in your code. You can access this mode by switching to the Java perspective and clicking on the Debug button in the toolbar of the Code view.
Reference: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Trace Debug mode – 7.3], [Java Debug mode – 7.3]
D, E
Explanation:
Trace Debug mode is a feature that allows you to trace each row processed by your job components and see the values of each column in each row. You can access this mode by opening the Debug Run tab of the Run view and clicking on Trace Debug button.
The capabilities that Trace Debug mode provides are:
Breaking when an input column fulfills a condition. You can set breakpoints on traces based on a condition or an expression that involves input data columns. For example, you can set a breakpoint to pause your job when a customer name contains a certain string or when a product price exceeds a certain value. To set a breakpoint based on a condition, you need to right-click on a trace on your job design workspace and select Show Breakpoint Setup option. This will open a dialog box where you can enter a condition or an expression for your breakpoint.
Advancing one row at a time. You can advance the execution of your job one row at a time by using the Step Over button in the toolbar of the Run view. This will allow you to see how each row is processed by your job components and how it affects the output data.
The capabilities that Trace Debug mode does not provide are:
Filtering which data is propagated by a flow. You cannot filter which data is propagated by a flow in Trace Debug mode. A flow is a link that shows the data transfer between components in your job design workspace. In Trace Debug mode, you can see the data flow on each trace and inspect the values of each column for each row processed by your job. However, you cannot change which rows are propagated by a flow based on a condition or an expression.
Advancing one column at a time. You cannot advance the execution of your job one column at a time in Trace Debug mode. You can only advance the execution of your job one row at a time by using the Step Over button in the toolbar of the Run view. This will allow you to see how each row is processed by your job components and how it affects the output data. However, you cannot see how each column is processed by your job components and how it affects the output data.
Breaking on a selected line of code. You cannot break on a selected line of code in Trace Debug mode. You can only break on a trace based on a condition or an expression that involves input data columns. To break on a selected line of code, you need to use Java Debug mode. Java Debug mode allows you to debug your job code in Java or Perl and see the values of each variable or expression in your code. You can access this mode by switching to the Java perspective and clicking on the Debug button in the toolbar of the Code view.
Reference: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Trace Debug mode – 7.3], [Java Debug mode – 7.3]
Question #4
Which aspects contribute to the calculation of the validity of a dataset? Choose 2 answers.
- A . Use of user ratings and certification
- B . Number of valid and invalid values across the dataset sample
- C . Use of semantic types across the dataset sample
- D . Number of empty rows across the dataset sample
Correct Answer: B, C
B, C
Explanation:
Comprehensive and Detailed
The validity of a dataset in Talend’s Trust Score™ framework is determined by:
Number of valid and invalid values across the dataset sample (Option B):
This metric assesses the quality of the data by evaluating the proportion of valid entries compared to invalid ones. A higher number of valid values indicates better data quality.
Use of semantic types across the dataset sample (Option C):
Semantic types help in understanding the meaning and context of data fields. Consistent and correct application of semantic types ensures that data is interpreted accurately, contributing to its validity.
Why not other options?
Option A: User ratings and certification pertain to the popularity axis, reflecting user trust and endorsement, not the intrinsic validity of the data.
Option D: The number of empty rows relates to the completeness axis, indicating missing data, rather than directly affecting validity.
Reference: Talend Cloud Data Inventory User Guide
B, C
Explanation:
Comprehensive and Detailed
The validity of a dataset in Talend’s Trust Score™ framework is determined by:
Number of valid and invalid values across the dataset sample (Option B):
This metric assesses the quality of the data by evaluating the proportion of valid entries compared to invalid ones. A higher number of valid values indicates better data quality.
Use of semantic types across the dataset sample (Option C):
Semantic types help in understanding the meaning and context of data fields. Consistent and correct application of semantic types ensures that data is interpreted accurately, contributing to its validity.
Why not other options?
Option A: User ratings and certification pertain to the popularity axis, reflecting user trust and endorsement, not the intrinsic validity of the data.
Option D: The number of empty rows relates to the completeness axis, indicating missing data, rather than directly affecting validity.
Reference: Talend Cloud Data Inventory User Guide
Question #5
In some instances, after applying changes to a component schema, you are asked if you would like to propagate the changes.
What is the significance of this prompt?
- A . Confirm that you want to apply the schema changes to the previous component in the Job.
- B . Confirm that you want to apply the schema changes to both the previous and next components in the Job.
- C . Confirm that you want to apply the schema changes to the next component in the Job.
- D . Confirm that you want to apply the schema changes to the selected component.
Correct Answer: C
C
Explanation:
When you modify the schema of a component in Talend Studio, the application prompts you to propagate these changes. This propagation ensures that any alterations to the data structure are
consistently applied throughout the Job, maintaining data integrity and coherence.
Understanding Schema Propagation:
Purpose: Schema propagation is essential to synchronize the data structure across connected components. When a schema changes (e.g., adding or removing a column), downstream components that rely on this schema need to be updated to reflect these changes.
Prompt Significance: The prompt serves as a confirmation to apply the schema changes to the subsequent components in the Job. By agreeing to propagate, Talend Studio automatically updates the schemas of all downstream components connected to the modified component.
Example Scenario:
Consider a Job where a tFileInputDelimited component reads data and passes it to a tMap component, which then outputs to a tFileOutputDelimited component. If you add a new column to the schema of tFileInputDelimited:
Modification:
You add a new column, ’emailAddress’, to the tFileInputDelimited schema.
Propagation Prompt:
Upon making this change, Talend Studio prompts you to propagate the schema changes.
Effect of Propagation:
By confirming, the ’emailAddress’ column is added to the schemas of all downstream components (e.g., tMap and tFileOutputDelimited). This ensures that these components recognize and can process the new column appropriately.
By understanding and utilizing schema propagation, you ensure that all components within your Talend Jobs remain synchronized, reducing errors and enhancing data processing efficiency.
Reference: Talend Official Documentation, Talend Schema Management Guide
C
Explanation:
When you modify the schema of a component in Talend Studio, the application prompts you to propagate these changes. This propagation ensures that any alterations to the data structure are
consistently applied throughout the Job, maintaining data integrity and coherence.
Understanding Schema Propagation:
Purpose: Schema propagation is essential to synchronize the data structure across connected components. When a schema changes (e.g., adding or removing a column), downstream components that rely on this schema need to be updated to reflect these changes.
Prompt Significance: The prompt serves as a confirmation to apply the schema changes to the subsequent components in the Job. By agreeing to propagate, Talend Studio automatically updates the schemas of all downstream components connected to the modified component.
Example Scenario:
Consider a Job where a tFileInputDelimited component reads data and passes it to a tMap component, which then outputs to a tFileOutputDelimited component. If you add a new column to the schema of tFileInputDelimited:
Modification:
You add a new column, ’emailAddress’, to the tFileInputDelimited schema.
Propagation Prompt:
Upon making this change, Talend Studio prompts you to propagate the schema changes.
Effect of Propagation:
By confirming, the ’emailAddress’ column is added to the schemas of all downstream components (e.g., tMap and tFileOutputDelimited). This ensures that these components recognize and can process the new column appropriately.
By understanding and utilizing schema propagation, you ensure that all components within your Talend Jobs remain synchronized, reducing errors and enhancing data processing efficiency.
Reference: Talend Official Documentation, Talend Schema Management Guide
Question #6
Which characteristics distinguish Traces Debug from Java Debug?
Choose 2 answers
- A . Allow row-by-row inspection of data flows
- B . Requires a separate perspective
- C . Require Java development experiences
- D . Supports breakpoints based on input data condition
Correct Answer: A, D
A, D
Explanation:
Trace Debug and Java Debug are two modes that allow you to debug your jobs in Talend Studio. Trace Debug mode allows you to trace each row processed by your job components and see the values of each column in each row. Java Debug mode allows you to debug your job code in Java or Perl and see the values of each variable or expression in your code.
The characteristics that distinguish Trace Debug from Java Debug are:
Trace Debug mode allows row-by-row inspection of data flows, while Java Debug mode does not. Data flows are the links that show the data transfer between components in your job design workspace. In Trace Debug mode, you can see the data flow on each trace and inspect the values of each column for each row processed by your job. You can also use filters to display only the rows that match a condition or an expression. In Java Debug mode, you cannot see the data flow on each trace or inspect the values of each column for each row.
Trace Debug mode supports breakpoints based on input data condition, while Java Debug mode does not. Breakpoints are points where the execution of your job pauses and waits for your action. You can
use breakpoints to inspect your data or debug your logic at specific points of your job execution. In Trace Debug mode, you can set breakpoints on traces based on a condition or an expression that involves input data columns. For example, you can set a breakpoint to pause your job when a customer name contains a certain string or when a product price exceeds a certain value. In Java Debug mode, you can only set breakpoints on lines of code based on a condition or an expression that involves variables or expressions.
The characteristics that do not distinguish Trace Debug from Java Debug are:
Both modes require a separate perspective. A perspective is a set of views and editors that are arranged in a specific way to support a specific task. In Talend Studio, you can switch between different perspectives, such as Integration, Debug, Profiling, etc. To use Trace Debug mode, you need to switch to the Debug perspective by clicking on the Open Perspective button and selecting Debug. To use Java Debug mode, you need to switch to the Java perspective by clicking on the Open Perspective button and selecting Java.
Neither mode requires Java development experience. Although Java Debug mode allows you to debug your job code in Java or Perl, you do not need to have Java development experience to use it. You can use the graphical interface of Talend Studio to design your job components and properties without writing any code. You can also use the Code view to see the generated code of your job in Java or Perl and modify it if needed. However, you do not need to write any code from scratch or understand all the details of the code to use Java Debug mode.
Reference: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Trace Debug mode – 7.3], [Java Debug mode – 7.3]
A, D
Explanation:
Trace Debug and Java Debug are two modes that allow you to debug your jobs in Talend Studio. Trace Debug mode allows you to trace each row processed by your job components and see the values of each column in each row. Java Debug mode allows you to debug your job code in Java or Perl and see the values of each variable or expression in your code.
The characteristics that distinguish Trace Debug from Java Debug are:
Trace Debug mode allows row-by-row inspection of data flows, while Java Debug mode does not. Data flows are the links that show the data transfer between components in your job design workspace. In Trace Debug mode, you can see the data flow on each trace and inspect the values of each column for each row processed by your job. You can also use filters to display only the rows that match a condition or an expression. In Java Debug mode, you cannot see the data flow on each trace or inspect the values of each column for each row.
Trace Debug mode supports breakpoints based on input data condition, while Java Debug mode does not. Breakpoints are points where the execution of your job pauses and waits for your action. You can
use breakpoints to inspect your data or debug your logic at specific points of your job execution. In Trace Debug mode, you can set breakpoints on traces based on a condition or an expression that involves input data columns. For example, you can set a breakpoint to pause your job when a customer name contains a certain string or when a product price exceeds a certain value. In Java Debug mode, you can only set breakpoints on lines of code based on a condition or an expression that involves variables or expressions.
The characteristics that do not distinguish Trace Debug from Java Debug are:
Both modes require a separate perspective. A perspective is a set of views and editors that are arranged in a specific way to support a specific task. In Talend Studio, you can switch between different perspectives, such as Integration, Debug, Profiling, etc. To use Trace Debug mode, you need to switch to the Debug perspective by clicking on the Open Perspective button and selecting Debug. To use Java Debug mode, you need to switch to the Java perspective by clicking on the Open Perspective button and selecting Java.
Neither mode requires Java development experience. Although Java Debug mode allows you to debug your job code in Java or Perl, you do not need to have Java development experience to use it. You can use the graphical interface of Talend Studio to design your job components and properties without writing any code. You can also use the Code view to see the generated code of your job in Java or Perl and modify it if needed. However, you do not need to write any code from scratch or understand all the details of the code to use Java Debug mode.
Reference: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Trace Debug mode – 7.3], [Java Debug mode – 7.3]
Question #7
You need to create a centralized metadata connection to a database server for an application.
Which steps should you take before building a Job that reads from that database? Choose 3 answers.
- A . Add a tCreateTable component to create a table in the database.
- B . Add a tMap component to handle and convert Db Types.
- C . Create Db Connections metadata to describe the database connection.
- D . Drag the Db Connections metadata onto the Designer to read from the database component.
- E . Retrieve the schemas from the database connection.
Correct Answer: C, D, E
C, D, E
Explanation:
Comprehensive and Detailed
To establish a centralized metadata connection to a database server in Talend Studio, follow these steps before constructing a Job that reads from the database:
Create Db Connections Metadata to Describe the Database Connection (Option C):
In the Repository panel, right-click on "Metadata" and select "Create connection."
Fill in the necessary details such as database type, host, port, database name, username, and password.
Test the connection to ensure it is configured correctly.
Save the connection metadata for reuse across multiple Jobs.
Retrieve the Schemas from the Database Connection (Option E):
After creating the database connection metadata, expand it to view the available schemas.
Retrieve the required schemas by importing the table structures.
This step ensures that the schema definitions are centralized and can be reused in different Jobs.
Drag the Db Connections Metadata onto the Designer to Read from the Database Component (Option D):
In the Repository, locate the previously created database connection metadata.
Drag and drop the desired table or schema onto the Designer workspace.
Talend Studio will automatically create the appropriate input component (e.g., tDBInput) configured with the connection and schema details.
By following these steps, you ensure a centralized and consistent approach to managing database connections and schemas, promoting reusability and reducing configuration errors.
Reference: Talend Studio User Guide, Talend Metadata Management Documentation
C, D, E
Explanation:
Comprehensive and Detailed
To establish a centralized metadata connection to a database server in Talend Studio, follow these steps before constructing a Job that reads from the database:
Create Db Connections Metadata to Describe the Database Connection (Option C):
In the Repository panel, right-click on "Metadata" and select "Create connection."
Fill in the necessary details such as database type, host, port, database name, username, and password.
Test the connection to ensure it is configured correctly.
Save the connection metadata for reuse across multiple Jobs.
Retrieve the Schemas from the Database Connection (Option E):
After creating the database connection metadata, expand it to view the available schemas.
Retrieve the required schemas by importing the table structures.
This step ensures that the schema definitions are centralized and can be reused in different Jobs.
Drag the Db Connections Metadata onto the Designer to Read from the Database Component (Option D):
In the Repository, locate the previously created database connection metadata.
Drag and drop the desired table or schema onto the Designer workspace.
Talend Studio will automatically create the appropriate input component (e.g., tDBInput) configured with the connection and schema details.
By following these steps, you ensure a centralized and consistent approach to managing database connections and schemas, promoting reusability and reducing configuration errors.
Reference: Talend Studio User Guide, Talend Metadata Management Documentation
Question #8
Which file should you edit to enable SSL for a JobServer?
- A . Conf/TalendJobServer.properties
- B . Conf/TalendServer.properties
- C . Conf/server.xml
- D . Jsl_stati64.ini
Correct Answer: A
A
Explanation:
To enable SSL for a JobServer, you need to edit the conf/TalendJobServer.properties file. A JobServer is a server application that allows you to execute jobs remotely from Talend Studio or Talend Administration Center. The conf/TalendJobServer.properties file contains various configuration parameters for your JobServer, such as port number, log level, security options, etc. To enable SSL for your JobServer, you need to set the ssl parameter to true and provide the path and password of your keystore file that contains your SSL certificate.
You do not need to edit conf/TalendServer.properties, conf/server.xml, or jsl_static64.ini files. These files are not related to JobServer configuration or SSL settings. The conf/TalendServer.properties file is used to configure Talend Administration Center settings, such as database connection, LDAP authentication, email notification, etc. The conf/server.xml file is used to configure Tomcat server settings, such as connectors, realms, valves, etc. The jsl_static64.ini file is used to configure Java Service Launcher settings, such as service name, description, startup type, etc.
Reference: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Configuring Talend JobServer –
A
Explanation:
To enable SSL for a JobServer, you need to edit the conf/TalendJobServer.properties file. A JobServer is a server application that allows you to execute jobs remotely from Talend Studio or Talend Administration Center. The conf/TalendJobServer.properties file contains various configuration parameters for your JobServer, such as port number, log level, security options, etc. To enable SSL for your JobServer, you need to set the ssl parameter to true and provide the path and password of your keystore file that contains your SSL certificate.
You do not need to edit conf/TalendServer.properties, conf/server.xml, or jsl_static64.ini files. These files are not related to JobServer configuration or SSL settings. The conf/TalendServer.properties file is used to configure Talend Administration Center settings, such as database connection, LDAP authentication, email notification, etc. The conf/server.xml file is used to configure Tomcat server settings, such as connectors, realms, valves, etc. The jsl_static64.ini file is used to configure Java Service Launcher settings, such as service name, description, startup type, etc.
Reference: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Configuring Talend JobServer –
Question #9
Which statements describe the Talend Cloud Data Inventory Trust Score™? Choose 2 answers.
- A . Aggregates several metrics into a single score.
- B . Helps data consumers assign a score representing the quality of the dataset.
- C . Scales the Trust Score from 0 to 5.
- D . Scales the Trust Score from 0 to 10.
Correct Answer: A, C
A, C
Explanation:
Comprehensive and Detailed
The Talend Trust Score™ is a feature of Talend Cloud Data Inventory that provides an assessment of a dataset’s reliability and quality:
Aggregates several metrics into a single score (Option A):
The Trust Score™ combines multiple factors, including validity, completeness, popularity, discoverability, and usage, into a single, comprehensive score. This aggregation helps users quickly gauge the overall trustworthiness of a dataset.
Scales the Trust Score from 0 to 5 (Option C):
The Trust Score™ ranges from 0 to 5, with higher scores indicating better data quality and reliability.
This standardized scale allows for easy comparison between datasets.
Why not other options?
Option B: While data consumers can view and utilize the Trust Score™, it is automatically calculated by Talend based on specific metrics; users do not assign this score themselves.
Option D: The Trust Score™ does not use a 0 to 10 scale; it specifically ranges from 0 to 5.
Reference: Talend Cloud Data Inventory User Guide, Talend Trust Score™ Overview
A, C
Explanation:
Comprehensive and Detailed
The Talend Trust Score™ is a feature of Talend Cloud Data Inventory that provides an assessment of a dataset’s reliability and quality:
Aggregates several metrics into a single score (Option A):
The Trust Score™ combines multiple factors, including validity, completeness, popularity, discoverability, and usage, into a single, comprehensive score. This aggregation helps users quickly gauge the overall trustworthiness of a dataset.
Scales the Trust Score from 0 to 5 (Option C):
The Trust Score™ ranges from 0 to 5, with higher scores indicating better data quality and reliability.
This standardized scale allows for easy comparison between datasets.
Why not other options?
Option B: While data consumers can view and utilize the Trust Score™, it is automatically calculated by Talend based on specific metrics; users do not assign this score themselves.
Option D: The Trust Score™ does not use a 0 to 10 scale; it specifically ranges from 0 to 5.
Reference: Talend Cloud Data Inventory User Guide, Talend Trust Score™ Overview
Question #10
You can initialize your component endpoint, API mappings, and documentation from your API definition.
Which API definitions are supported by tRESTRequest?
- A . CSV definition file
- B . XML definition file
- C . WSDL file
- D . OAS/Swagger 2.0 file
Correct Answer: D
D
Explanation:
Comprehensive and Detailed
The tRESTRequest component supports OpenAPI Specification (OAS)/Swagger 2.0 for initializing component endpoints, API mappings, and documentation.
OAS/Swagger 2.0 file (Correct Answer – Option D):
tRESTRequest allows API-first development by importing a Swagger 2.0 (OAS) definition.
This enables automatic configuration of API endpoints, request parameters, and response structures.
Why not other options?
CSV definition file (Option A): Not a valid API definition format.
XML definition file (Option B): XML files are not standard for REST API definitions.
WSDL file (Option C): WSDL is used for SOAP-based web services, not REST.
Reference: Talend API Development Guide, Talend REST Component Documentation
D
Explanation:
Comprehensive and Detailed
The tRESTRequest component supports OpenAPI Specification (OAS)/Swagger 2.0 for initializing component endpoints, API mappings, and documentation.
OAS/Swagger 2.0 file (Correct Answer – Option D):
tRESTRequest allows API-first development by importing a Swagger 2.0 (OAS) definition.
This enables automatic configuration of API endpoints, request parameters, and response structures.
Why not other options?
CSV definition file (Option A): Not a valid API definition format.
XML definition file (Option B): XML files are not standard for REST API definitions.
WSDL file (Option C): WSDL is used for SOAP-based web services, not REST.
Reference: Talend API Development Guide, Talend REST Component Documentation