Qlik QSDA2019 (Qlik Sense Data Architect Certification) Certification Exam is designed to test the skills and knowledge of individuals who work with Qlik Sense data modeling, data visualization, and data analysis. QSDA2019 exam is intended for data architects, business analysts, BI developers, and IT professionals who use Qlik Sense to build data models, create visualizations, and analyze data.
The QSDA2019 certification exam assesses candidates on their ability to create efficient data models using best practices, manage data and data relationships effectively, create optimized data connections, and manage and optimize the performance of data models. QSDA2019 exam consists of multiple-choice questions that test the candidates’ proficiency in Qlik Sense data architecture. Candidates who pass the exam will receive the Qlik Sense Data Architect certification, indicating that they have demonstrated proficiency in the skills required for designing and implementing data models with Qlik Sense.
Reference: https://www.qlik.com/us/services/training/certifications-and-qualifications
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Qlik QSDA2019 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design Data Models | 30% | - Implement calendars, flags, and set analysis support structures - Determine appropriate data model architecture - Manage complex modeling scenarios - Design scalable and reusable data models |
| Topic 2: Identify Model Requirements | 10% | - Identify Qlik Sense features to meet business requirements - Identify data load and refresh requirements - Determine security requirements |
| Topic 3: Validate Data | 20% | - Resolve data quality and formatting issues - Resolve synthetic keys and circular references - Validate data models against source systems - Debug and troubleshoot script errors |
| Topic 4: Build Data Models | 40% | - Implement Section Access security - Perform joins, keeps, resident loads, and incremental loads - Use data transformation techniques in Data Load Editor and Data Manager - Manage data connections and data sources - Create and transform data models using load scripts |







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