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Outline

The Qlik Compose certification exam measures your ability to design, implement, and support automated data warehouse and data lake solutions within the Qlik Data Integration Compose platform.

Certification Exam details 
Duration: 120 minutes 
Number of questions: 55 
Passing score: 70% 

Exam content is updated periodically. The number and difficulty of questions may change. The passing score is adjusted to maintain a consistent standard. 

Recommended experience

  • Minimum of 2-3 years experience implementing data warehouse and/or data lake solutions 
  • Knowledge of data warehouse architectures and all phases of the data warehouse development life cycle
  • Ability to interpret business requirements into viable solutions
  • Preparation

  • Instructor-Led Training:Review available training 
  • Qlik Continuous Classroom Qlik Data Integration Courses
  • Badge 

    After passing this certification exam, you are awarded the Qlik Compose Certification Exam badge. To learn more about the criteria for earning this badge, visit our Credly badging page.

    Certification Exam topics

    Architecture (24%)

  • Identify different components of the Qlik Compose data architecture.
  • Distinguish between the Qlik Compose data lake view options.
  • Identify supported data storage and processing combinations in Qlik Compose.
  • Identify how Qlik Compose and Qlik Replicate are integrated.
  • Modeling (30%)

  • Demonstrate an understanding of how to build a logical warehouse model in the solution.
  • Define data lake entities in Qlik Compose.
  • Determine how to design data marts in Qlik Compose.
  • Identify the logical model's impact on physical structures.
  • Data Integration and Mapping (34%)

  • Identify what is automated in the ETL for data warehouse and data lake projects.
  • Evaluate data warehouse mappings and ETL sets.
  • Demonstrate an understanding of data lake mappings and storage tasks.
  • Demonstrate an understanding of how to implement data transformations.
  • Demonstrate an understanding of data cleansing and validation rules.
  • Administration and Operations (12%)

  • Define workflows and scheduling.
  • Determine how to manage source control and deployment packages.
  • Determine how to monitor operations.