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Test Number : QSDA2018
Test Name : Qlik Sense Data Architect Certification Exam
Vendor Name : Qlik
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The Qlik Sense Data Architect Certification test measures your ability to identify requirements for data models, design and build data models, and validate the data. This test has 50 multiple-choice questions to answer in 2 hours.

Prerequisites
- Practical experience developing multiple production-quality applications in Qlik Sense
- Ability to write Qlik Sense LOAD scripts and validate data
- Basic understanding of Extract-Transform-Load (ETL)
- Create and use connectors to various data sources
- Understand the QVD layer and architecture of the Qlik platform
- Ability to architect data to provide optimal performance
- Familiar with SQL and relational databases

Exam Topics
Identify Requirements for Data Models (16% of the exam)
- Identify the data load and refresh requirements (e.g., tiered architecture, multiple data sources, varying refresh times)
- Given a scenario, identify Qlik Sense features to meet customer needs (e.g., associative data model, master items, ODAG, GeoAnalytics)
- Outline steps to implement security requirements

Design Data Models (28% of the exam)
- Determine an appropriate data model design to meet customer needs
- Decide on an appropriate data model that prioritizes reuse, scalability, and efficiency (e.g., tiered architecture, data governance)
- Determine how to manage complex scenarios (e.g., calendar, set analysis, flags, functions)

Build Data Models (34% of the exam)
- Create data models (e.g., join, keep, resident load, where clause, incremental load, purge strategy, variable)
- Given a scenario, use data transformation techniques with both data load editor and data manager
- Manage security using section access
- Use the Qlik Converter to migrate QlikView documents to Qlik Sense applications
- Use appropriate data connections

Validate Data (22% of the exam)
- Validate data models against source information using Qlik Sense visualizations
- Resolve data modeling issues (e.g., synthetic keys, circular references, scripting errors, debugging)
- Resolve data issues (e.g., null values, data formatting)



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