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Qlik QSDA2019 certification exam is a great way to demonstrate your expertise in Qlik Sense data architecture. It is a challenging exam that requires a solid understanding of data modeling, design, and implementation with Qlik Sense. With the right preparation, you can pass the exam and earn your QSDA2019 certification, which will open up new opportunities in your career.
Reference: https://www.qlik.com/us/services/training/certifications-and-qualifications
Passing the Qlik QSDA2019 exam is a great achievement for individuals who are seeking to enhance their career in the field of data architecture. Qlik Sense Data Architect Certification Exam certification demonstrates that the candidate has a comprehensive understanding of Qlik Sense, and can design and implement data architectures that meet business requirements. It also helps individuals stand out in the competitive job market and opens up new opportunities for career advancement.
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The QSDA2019 exam consists of 50 multiple-choice questions that are designed to test the candidate's knowledge and skills in data modeling, data analysis, and data visualization using Qlik Sense. QSDA2019 exam covers a wide range of topics, including data modeling concepts, creating and managing data connections, designing data models, building data visualizations, and managing Qlik Sense environments. Candidates who pass the QSDA2019 exam will gain a globally recognized certification that demonstrates their expertise in Qlik Sense and their ability to design and manage effective data models and dashboards.
Qlik QSDA2019 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Connectivity | 8% | - Use appropriate connectors and data connections - Manage connection configurations |
| Data Validation & Security | 16% | - Validate data accuracy and consistency - Migrate QlikView applications using Qlik Converter - Implement Section Access and security rules |
| Identify Model Requirements | 10% | - Identify business and technical requirements - Determine data sources and connectivity needs - Define security and access requirements |
| Data Transformations | 38% | - Handle dates, null values, and calculations - Use Data Load Editor and Data Manager - Document and maintain load scripts - Implement scripting and data cleansing |
| Data Model Design | 28% | - Design efficient and scalable data models - Plan for reuse and maintainability - Optimize data structures and relationships |








