Qlik View Data Architect Certification Practice Exam

Qlik View Data Architect Certification Practice Exam

The Qlik View Data Architect Certification is a professional level certification from Qlik whch certifies your skills to design and implement data models in QlikView. The certification attests to your skills for creating efficient data architectures and managing data sources, for data analysis and reporting. The certification includes data loading techniques, scripting, and best practices for developing data models for performance and usability in analytics.
Why is Qlik View Data Architect Certification important?

• Validates expertise in data modeling and architecture within the QlikView environment.
• Enhances career opportunities in data architecture and business intelligence roles.
• Demonstrates proficiency in best practices for data management and visualization in QlikView.
• Helps organizations identify qualified data architects capable of optimizing QlikView implementations.
• Contributes to professional credibility and recognition in the Qlik community.

Who should take the Qlik View Data Architect Certification Exam?

• Data Architect
• QlikView Developer
• Business Intelligence Architect
• Data Analyst
• Database Administrator

Skills Evaluated

Candidates taking the certification exam on the Qlik View Data Architect Certification is evaluated for the following skills:

• Data modeling and schema design
• Data loading and transformation techniques
• Scripting in QlikView for data manipulation
• Optimization of data models for performance
• Best practices in data governance and management
• Integration of data from multiple sources

Qlik View Data Architect Certification Certification Course Outline

The Qlik View Data Architect Certification Certification covers the following topics -

Module 1. Identify Requirements for Data Models

• Data load and refresh requirements

• Qlik Sense features to meet customer needs

• Implement security requirements

Module 2. Design Data Models

• SUitable data model design to meet customer needs

• Data model which prioritizes reuse, scalability, and efficiency

• Manage complex scenarios

Module 3. Build Data Models

• Create data models

• Data transformation techniques with both data load editor and data manager

• Security using section access management

• Qlik Converter for migrating QlikView documents to Qlik Sense applications

• Suitable data connections usage

Module 4. Validate Data

• Using Qlik Sense visualizations to validate data models against source information

• Data modeling issues resolution

• Data issues resolution