TDICDTS Practice Test and Study Guide
Qlik TDICDTS Exam Specifications
- Exam Code:
- TDICDTS
- Exam Name:
- Qlik Talend Data Integration Developer Using Talend Studio
- Provider:
- Qlik
- Time:
- 90 min
- Passing Percentage:
- 80%
- Version:
- 6.0
Question Types
- 90 Single Select
90 Questions with Answers
- PDF Printable (Q & A)
- 3 Months
Key Features to Key Benefits
Real Exam-like Questions and Answers (90 total)
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Comprehensive Coverage of Objectives
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Regularly Updated Content
Free Demo Questions Available
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Skills Covered in Qlik Talend Data Integration Developer Using Talend Studio (TDICDTS)
The Qlik Talend Data Integration Developer exam assesses your ability to design and assemble Talend Studio data pipelines, define clear control flow and orchestration for jobs and subjobs, and build robust connections to relational databases, flat files, JSON/XML and cloud services while embedding data quality checks and cleansing. It also tests skills in handling errors with retry and logging strategies, tuning performance through efficient design and parallelism, managing deployment and scheduling with environment versioning, preserving data lineage and metadata, documenting for maintainability, and debugging and optimizing transformation logic.
Essential Skills
- Understand core data integration concepts, including ETL and ELT patterns, data quality, and profiling.
- Design and assemble data integration jobs and subjobs with clear control flow and orchestration.
- Leverage key transformation components for mapping, joining, filtering, and aggregating data.
- Create robust data connections to diverse sources such as relational databases, flat files, JSON/XML, and cloud services.
- Implement data quality checks, validation rules, and data cleansing techniques.
- Configure error handling, retry strategies, and comprehensive logging for reliable data movement.
- Tune performance through efficient job design, parallel processing, and resource configuration.
- Manage deployment, scheduling, and environment versioning for production workflows.
- Preserve data lineage and metadata, and document jobs for maintainability.
- Debug efficiently using built-in tools, identify common issues, and optimize transformation logic.
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