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Passing the Qlik QSDA2022 certification exam demonstrates a strong understanding of Qlik Sense data architecture and can help data architects advance their careers. Certified professionals are recognized for their expertise in Qlik Sense data architecture and are in high demand in the industry. Certified professionals also have access to exclusive Qlik resources and events, which can further enhance their skills and knowledge.
Qlik QSDA2022 certification exam is a globally recognized certification that validates the candidate's expertise in data architecture using Qlik Sense. QSDA2022 exam is designed for data architects, data analysts, and business intelligence professionals who want to demonstrate their skills in data modeling, data integration, and data transformation. QSDA2022 exam is proctored, timed, and consists of multiple-choice questions. Candidates who pass the exam will receive a certificate that demonstrates their proficiency in Qlik Sense data architecture.
Reference: https://www.qlik.com/us/services/training/certifications-and-qualifications
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Qlik QSDA2022 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Model Design | 28% | - Define measures, attributes and relationships - Optimize model performance and efficiency - Choose appropriate data model architecture - Implement QVD layer architecture |
| Topic 2: Data Connectivity | 8% | - Identify required data sources and connectors - Configure and manage data connections |
| Topic 3: Data Transformations | 38% | - Perform data cleansing and formatting - Handle dates, nulls and complex transformations - Write and structure LOAD scripts - Organize and document scripts - Implement incremental loading |
| Topic 4: Identify Requirements | 22% | - Determine security and access requirements - Define dimensionality and slowly changing dimensions - Determine metrics, granularity and aggregation - Identify stakeholders and business requirements |
| Topic 5: Validation | 4% | - Validate data accuracy and completeness - Test scripts and data loads |
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