TALEND-CORE-DEVELOPER PREPARATION STORE & TALEND-CORE-DEVELOPER RELIABLE TEST PRICE

Talend-Core-Developer Preparation Store & Talend-Core-Developer Reliable Test Price

Talend-Core-Developer Preparation Store & Talend-Core-Developer Reliable Test Price

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Talend Core Certified Developer Exam Sample Questions (Q55-Q60):

NEW QUESTION # 55
Which statements are true when comparing a Joblet to a tRunJob component?
Choose 3 answers

  • A. The performance of a Joblet if better than running an equivalent Job using a tRunJob component.
  • B. Building a Joblet typically requires the use of generic input, and trigger component.
  • C. The nested Job called by a tRunJob component cannot use the same context variable of the Job in which it is used.
  • D. A Joblet uses the same context variables of the Job in which it is used, unlinke a tRunJob component.
  • E. The performance of tRunJob component is better than running an equivalent Job using a Joblet.

Answer: B,C,D

Explanation:
A Joblet is a reusable piece of a job that can be used in multiple jobs as a single component. A tRunJob component is a component that allows you to call another job as a subjob within a parent job. When comparing a Joblet to a tRunJob component, these statements are true:
* A Joblet uses the same context variables of the job in which it is used, unlike a tRunJob component. A context variable is a variable that can store a value that can be changed at runtime or between different contexts. A Joblet inherits the context variables from the job that contains it and does not have its own context variables. A tRunJob component can pass context variables from the parent job to the child job, or use a specific context for the child job.
* Building a Joblet typically requires the use of generic input and trigger components. A Joblet can have one or more input and output flows that connect it with other components in a job. To create these flows, you need to use generic input and trigger components, such as tJobletInput, tJobletOutput, tJobletTriggerInput, and tJobletTriggerOutput. These components allow you todefine schemas and triggers for your Joblet without depending on specific components.
* The nested job called by a tRunJob component cannot use the same context variables of the job in which it is used. A nested job is a job that is called by another job using a tRunJob component. A nested job can have its own context variables or receive context variables from its parent job, but it cannot use the same context variables as its parent job. This means that if you have two context variables with the same name in both jobs, they will be treated as separate variables and will not share values.
These statements are false when comparing a Joblet to a tRunJob component:
* The performance of tRunJob component is better than running an equivalent job using a Joblet. The performance of a Joblet is better than running an equivalent job using a tRunJob component. This is because a Joblet is integrated into the main code of the job and does not require launching another JVM process or loading another metadata object like a tRunJob component does. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Joblets - 7.3], [tRunJob properties - 7.3],
[Contexts - 7.3]


NEW QUESTION # 56
Which actions can you perform in the configuration panel in Pipeline Designer? Choose 2 answers.

  • A. Display and update dataset connections.
  • B. Select the settings for a pipeline export.
  • C. Modify processor values.
  • D. Preview changes made by processors.

Answer: A,C

Explanation:
Comprehensive and Detailed Explanation:
In Talend Pipeline Designer, theconfiguration panelprovides options for managing and modifying the settings of components within a pipeline.
* Modify processor values (Option A):
* Users can adjust values for processors such as filters, joins, transformations, and aggregations within the configuration panel.
* This helps fine-tune data processing rules directly in the pipeline.
* Display and update dataset connections (Option B):
* The configuration panel allows users to change dataset connections, updating the source or target locations of data.
* Users can modify database credentials, file paths, or API endpoints as needed.
Why not other options?
* Option C:The ability to preview changes made by processors is handled in thepreview panel, not the configuration panel.
* Option D:Pipeline export settings are managed separately in theexport settings menu, not in the configuration panel.


NEW QUESTION # 57
You need to call a different Job within a Job you are developing.
Which mechanism allows you to pass the parameters to the lob you want to call?

  • A. CommandLine options
  • B. Java Function paramters
  • C. File
  • D. Context parameters

Answer: D

Explanation:
To call a different job within a job you are developing, you can use the tRunJob component. This component allows you to execute another job as a subjob within a parent job. To pass the parameters to the job you want to call, you can use the context parameters. Context parameters are variables that can store values that can be changed at runtime or between different contexts. You can define context parameters in the Contexts tab of your job and assign them values for each context. You can also pass context parameters from the parent job to the child job by using the Context Param tab of the tRunJob component. This way, you can parameterize the properties or expressions of the child job with the values from the parent job.
You do not need to use a file, command line options, or Java function parameters to pass parameters to a different job. These methods are not supported by Talend Studio and may cause errors or unexpected results. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [tRunJob properties - 7.3], [Contexts - 7.3]


NEW QUESTION # 58
Which aspects contribute to the calculation of the validity of a dataset? Choose 2 answers.

  • A. Number of empty rows across the dataset sample
  • B. Use of user ratings and certification
  • C. Number of valid and invalid values across the dataset sample
  • D. Use of semantic types across the dataset sample

Answer: C,D

Explanation:
Comprehensive and Detailed Explanation:
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.


NEW QUESTION # 59
Whatare the key capabilities of Talend Cloud Data Preparation that improve data quality and accessibility?
Choose 2 answers

  • A. Cleanse data
  • B. Standardize data
  • C. Transform
  • D. Discover

Answer: A,B


NEW QUESTION # 60
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