Last Updated: Aug 01, 2026
No. of Questions: 80 Questions & Answers with Testing Engine
Download Limit: Unlimited
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| Level: | Associate |
| Sub-solution: | BusinessObjects: Data Services |
| Cut Score: | 68% |
| Exam: | 80 questions |
| Duration: | 180 mins |
| Component: | Data Integrator |
| Sample Questions: | SAP C_DS_42 Exam Sample Question |
| Languages: | English |
The "SAP Certified Application Associate - Data Integration with SAP Data Services 4.2" certification exam verifies that the candidate possesses proven skills and fundamental knowledge in implementing ETL projects, administering and managing projects using SAP Data Services. This exam will measure the candidate's knowledge of SAP DataServices starting with understanding Data Integration concepts, and will test required skills in applying performance tuning and sizing methods, implementing complex design methodology, performing Data Transformation and troubleshooting and recovery.
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| Topic Areas | Topic Details, Courses, Books |
|---|---|
| Change Data Capture < 8% | Compare Delta Load Methods, and implement source based Change Data Capture and target based Change Data Capture. |
| Basic Data Transformation > 12% | Use Target table options, built-in functions, the platform, validation and Query transforms, create batch jobs, describe data services object hierarchy/relationsihp and operation codes. |
| Data Integration Concepts < 8% | Descibe ETL Project Guidelines, Real-Time processing, and profile data in Data Services. |
| Recovery and Troubleshooting > 12% | Design recovery, troubleshoot/test jobs, apply error handling, explain Trace logs, and use the interactive debugger. |
| Data Management > 12% | Manage repositories, setup Data Stores and use the data services management console, install and configure data services, set up file formats, schedule jobs, manage Security in Data Services, and use Data Services Workbench. |
| Advanced Data Transformation 8% - 12% | Apply data integrator transforms, audit data flows, and use scripting and embedded Data Flows. |
| Performance Optimized Design > 12% | Optimize data flow for performance and measure performance, use parallel processing, push down operations, and distribute Data Flow execution across Job Servers; configure Bulk Loaders. |
| Complex Design Methodology 8% - 12% | Design the interdependancies within a workflow, use workflows to control the execution of the job, and implement Datastore configurations and System Configurations. |
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