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Talend-Core-Developer Practice Test Pdf | Talend-Core-Developer Exam Preview

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Talend Core Certified Developer Exam Sample Questions (Q50-Q55):

NEW QUESTION # 50
Which Action on table operations are supported by a tMysqlOutput component? Choose 3 answers.

A. Replace
B. Drop table
C. Create table
D. Drop table if exists and create
E. Create table if does not exist

Answer: C,D,E

Explanation:
Comprehensive and Detailed Explanation:
The tMysqlOutput component in Talend provides several actions on tables to manage data output operations effectively. The supported actions include:
* Drop Table if Exists and Create (Option B):
* This action checks if the specified table exists in the database. If it does, the table is dropped and a new one is created. This ensures that the table is recreated fresh for the data load.
* Create Table if Does Not Exist (Option D):
* This action checks if the specified table exists in the database. If it does not exist, the table is created. If it already exists, no action is taken, and the existing table is used.
* Create Table (Option E):
* This action attempts to create the specified table in the database. If the table already exists, an error will occur unless handled appropriately.
These actions provide flexibility in managing database tables during data integration processes, allowing for dynamic table creation and management based on the Job's requirements.

NEW QUESTION # 51
Which aspects contribute to the calculation of the validity of a dataset? Choose 2 answers.

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

Answer: A,C

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 # 52
You want to create a generic schema using a schema defined in a Talend component in the Repository view.
How can you accomplish this?

A. By right-clicking the component and selecting the Generic schema option.
B. In the Schema Editor window for the component.
C. In the Repository, by right-clicking Generic schemas.
D. On the Advanced settings tab of the Component view.

Answer: C

Explanation:
To create a generic schema from a schema defined in a Talend component, follow these steps:
* Open the Repository View:
* In Talend Studio, navigate to the Repository panel, typically located on the left side of the interface.
* Locate the 'Generic schemas' Node:
* Within the Repository, expand the 'Metadata' section to find the 'Generic schemas' node.
* Initiate the Generic Schema Creation Process:
* Right-click on 'Generic schemas' and select 'Create generic schema' from the context menu.
* Define the Schema Properties:
* In the schema creation wizard that appears, provide the necessary properties such as 'Name' and
'Description' for the new generic schema.
* Set Up the Schema Structure:
* Define the schema structure by adding columns and specifying their data types as required.
* Finalize the Schema Creation:
* Click 'Finish' to complete the creation process. The new generic schema will now be available under the 'Generic schemas' node in the Repository.
This method allows you to create a reusable generic schema that can be applied across multiple components and Jobs within Talend Studio.

NEW QUESTION # 53
What is the generic Input component used for in a Joblet design?

A. Carrying data into a subJob
B. Carrying data into a Joblet
C. Triggering a subJob
D. Triggering a Joblet

Answer: B

Explanation:
The generic Input component used for in a Joblet design is the tJobletInput component. This component is used to carry data into a Joblet from another component in the job that contains the Joblet. A Joblet is a reusable piece of a job that can be used in multiple jobs as a single component. 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 output components, such as tJobletInput, tJobletOutput, tJobletTriggerInput, and tJobletTriggerOutput. These components allow you to define schemas and triggers for your Joblet without depending on specific components.
The tJobletInput component is not used for triggering a Joblet, triggering a subjob, or carrying data into a subjob. These are different concepts and functionalities in Talend Studio. A trigger is a link that activates a subjob or a component based on a condition or an event. A subjob is a part of a job that consists of one or more components connected by data flows or triggers. A subjob can be triggered by another subjob using triggers such as OnSubjobOk, OnSubjobError, Run if, etc. A subjob can also carry data into another subjob using data flows such as main, lookup, reject, etc. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [tJobletInput properties - 7.3], [Joblets - 7.3], [Triggers - 7.3]

NEW QUESTION # 54
What are the key capabilities of Talend Cloud Data Preparation that improve data quality and accessibility? Choose 3 answers.

A. Standardize data
B. Format data
C. Cleanse data
D. Transform
E. Discover

Answer: A,C,D

Explanation:
Comprehensive and Detailed Explanation:
Talend Cloud Data Preparation enhances data quality and accessibility through:
* Cleanse data (Option C):
* Identifying and correcting inaccuracies or inconsistencies to ensure data integrity.
* Transform (Option D):
* Modifying data structures or values to meet specific requirements or formats.
* Standardize data (Option E):
* Ensuring uniformity in data presentation and format, facilitating consistency across datasets.
Why not other options?
* Option A: Discovery is typically associated with data profiling, not preparation.
* Option B: Formatting is a subset of transformation and standardization processes.

NEW QUESTION # 55
......

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