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Qlik QSDA2022 exam is a certification exam for data professionals who want to validate their knowledge and expertise in Qlik Sense data architecture. QSDA2022 exam is designed to test the candidate’s proficiency in designing, developing, and deploying Qlik Sense data models. The QSDA2022 exam is the latest version of the QSDA certification exam and it incorporates the latest features and functionalities of the Qlik Sense platform.
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To prepare for the QSDA2022 certification exam, candidates should have a strong understanding of Qlik Sense data architecture and be familiar with the platform's features and functionality. They should also have experience working with data and be comfortable using Qlik Sense to visualize and analyze data. Qlik offers a range of training courses and resources to help candidates prepare for the exam, including online courses, virtual instructor-led training, and self-paced learning modules.
Qlik Sense Data Architect Certification Exam 2022, also known as QSDA2022, is a certification exam designed for individuals who want to demonstrate their expertise in designing and managing data architectures using the Qlik Sense platform. QSDA2022 exam is a comprehensive assessment of an individual's knowledge and skills in data architecture, data modeling, scripting, data integration, and data security. Passing QSDA2022 exam demonstrates that an individual is a qualified data architect who can design and implement data architectures that meet the needs of modern businesses.
Reference: https://www.qlik.com/us/services/training/certifications-and-qualifications
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Qlik QSDA2022 is the latest certification exam for Qlik Sense Data Architect. QSDA2022 exam is designed to test the knowledge and skills of data architects who work with Qlik Sense. QSDA2022 exam covers a wide range of topics related to data architecture, including data modeling, data integration, data transformation, and data governance. Passing this certification exam demonstrates a strong understanding of Qlik Sense data architecture and the ability to design and implement scalable data solutions.
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify Requirements | 20% | - Determine metrics, granularity and aggregation - Determine appropriate level of security - Identify dimensionality and slowly changing dimension support - Identify stakeholders in scenarios - Determine primary requirements with business users |
| Topic 2: Data Connectivity | 8% | - Determine data sources and connectors needed - Choose appropriate connection methods |
| Topic 3: Validation | 6% | - Validate and test data - Validate and test scripts |
| Topic 4: Data Model Design | 28% | - Efficient implementation of data structures - Optimize data model for Qlik Sense - Select appropriate data model types - Determine measures and attributes from sources |
| Topic 5: Data Transformations | 38% | - Incremental loading for extract layer - Document load scripts properly - Build data content based on requirements - Handle null and blank data for filtering - Date handling techniques - Script organization and cleansing |
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