Qlik QSDA2018 Deutsch Exam Details & Actual Exam Questions
- Exam Code/Number: QSDA2018 Deutsch
- Exam Name/Title: Qlik Sense Data Architect Certification Exam - June 2018 Release (QSDA2018 Deutsch Version)
- Certification Provider: Qlik
- Corresponding Certification: Qlik Sense Data Architect
- Exam Questions: 52
- Updated On: Jul,20 2026
- Certification Level: Professional
Qlik Sense Data Architect Certification Exam - June 2018 Release (QSDA2018 Deutsch Version) Exam Questions
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Qlik QSDA2018 Deutsch Exam Overview:
| Certification Vendor: | Qlik |
| Exam Name: | Qlik Sense Data Architect Certification Exam - June 2018 Release |
| Exam Number: | QSDA2018 |
| Exam Format: | Multiple choice, Multiple response, Scenario-based |
| Passing Score: | 58% |
| Related Certifications: | Qlik Sense Business Analyst Qlik Sense System Administrator |
| Certificate Validity Period: | 2 years |
| Exam Price: | USD 250 |
| Exam Duration: | 120 minutes |
| Available Languages: | English |
| Real Exam Qty: | 50 |
| Recommended Training: | Qlik Sense Data Architect Training |
| Exam Registration: | Qlik Official Certification Page Pearson VUE Registration |
| Sample Questions: | Qlik QSDA2018 Deutsch Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No mandatory prerequisites; Qlik recommends hands-on experience with Qlik Sense and completion of related training courses |
| Official Syllabus URL: | https://www.qlik.com/us/services/training/certification |
Qlik QSDA2018 Deutsch Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Qlik Sense Architecture and Data Connections | 20% | - Data connectivity (files, databases, web sources, APIs) - Managing connections and data sources - Qlik Sense platform architecture |
| Topic 2: Scripting and Data Load Editor | 25% | - Debugging and troubleshooting scripts - Managing data load scripts - Variables, functions, and expressions - Script syntax and control statements |
| Topic 3: Data Modeling and Transformation | 30% | - Using QVD files and incremental loading - Designing efficient data models - Data transformation, cleansing, and enrichment - Resolving synthetic keys and circular references |
| Topic 4: Security and Governance | 15% | - Section Access and data security - Application and stream security - Data governance best practices |
| Topic 5: Performance Optimization and Validation | 10% | - Validating data integrity and consistency - Monitoring and improving application performance - Optimizing data model and script performance |
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