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Talend-Core-Developer Exam Syllabus

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Before starting your Talend-Core-Developer exam preparation, it is recommended to review the complete Talend Core Certified Developer Exam syllabus and carefully go through the exam objectives listed below. Once you understand the exam structure and objectives, you should practice using our free Talend-Core-Developer questions. We also provide premium Talend-Core-Developer practice test, fully updated according to the latest exam objectives, to help you accurately assess your preparedness for the actual exam.

Talend
Vendor
Talend-Core-Developer
Exam Code
55
Total Questions
10
Total Exam Domains

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Talend-Core-Developer EXAM QUESTIONS

Talend-Core-Developer Exam Objectives

Section 1: Getting Started with Data Integration
Weight:
-
  • Measures the skills of Data Integration Developers.
  • Covers fundamental concepts of Talend Data Integration.
  • Includes understanding the Talend Studio GUI.
  • Involves defining data integration workflows.
  • Focuses on creating basic jobs for data processing.
Section 2: Joining and Filtering Data
Weight:
-
  • Measures the skills of ETL Developers.
  • Covers handling data from multiple sources.
  • Includes defining and managing metadata.
  • Involves joining datasets using the tMap component.
  • Covers configuring join settings and filtering data based on conditions.
  • Focuses on managing rejected records efficiently.
Section 3: Error Handling
Weight:
-
  • Measures the skills of Data Engineers.
  • Covers strategies for managing errors in data workflows.
  • Includes using triggers to control job execution sequences.
  • Involves incorporating logging components to monitor processes.
  • Focuses on implementing conditional triggers based on component variables.
Section 4: Orchestrating Jobs
Weight:
-
  • Measures the skills of ETL Architects.
  • Covers job orchestration techniques.
  • Includes understanding master jobs and passing parameters using context variables.
  • Involves managing job dependencies and implementing joblets for reusable workflows.
  • Covers parallel execution strategies and profiling job performance for optimization.
Section 5: Project Management
Weight:
-
Measures the skills of Project Managers.
Focuses on handling Talend projects in a collaborative environment.
Includes working with local and remote connections.
Covers configuring version control systems such as Git.
Involves performing revision control operations.
Uses reference projects to streamline development processes.
Section 6: Working with Files
Weight:
-
  • Measures the skills of Data Analysts.
  • Covers file-based data processing.
  • Includes configuring components and defining schemas.
  • Involves performing data mapping using the tMap component.
  • Focuses on applying built-in Talend functions to transform data efficiently.
Section 7: Using Context Variables
Weight:
-
  • Measures the skills of Data Integration Developers.
  • Covers using context variables to create flexible and dynamic jobs.
  • Includes defining and using context variables within workflows.
  • Involves executing jobs in different environments based on runtime configurations.
Section 8: Working with Databases
Weight:
-
  • Measures the skills of Database Administrators.
  • Covers database integration within Talend.
  • Includes defining database metadata and managing database actions.
  • Involves writing custom SQL queries.
  • Focuses on incorporating metadata, generic schemas, and context variables in database operations.
Section 9: Deploying Jobs
Weight:
-
  • Measures the skills of Cloud Engineers.
  • Focuses on deploying Talend jobs in production environments.
  • Includes building and running jobs as standalone applications.
  • Covers handling context variables in deployed jobs.
  • Involves configuring remote execution environments and launching jobs on external servers.
Section 10: Debugging
Weight:
-
  •  Covers debugging techniques to ensure job accuracy and efficiency.
  • Includes using trace debugging to monitor job execution.
  • Involves identifying errors and troubleshooting issues within data workflows.
  • Focuses on maintaining smooth processing.