Qlik Sense Data Architect Certification

Duration: Hours

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    Training Mode: Online

    Description

    The Qlik Sense Data Architect Certification Exam measures your ability to identify requirements for data models, design and build data models, and validate the data. This exam is platform neutral, which means that the content applies to both the client managed and SaaS editions of Qlik Sense. This exam 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

     

    Recommended Preparation Resources

    • Instructor-Led Training: Data Modeling for Qlik Sense
    • Qlik Continuous Classroom – Data Architect
    • FREE Qlik Sense Data Architect Certification Practice Questions

     

    Exam Topics

    Identify Requirements (20% of the exam)

    • Determine primary requirements with business users.
    • Given a scenario, choose stakeholders.
    • Given a scenario, determine metrics and levels of granularity and aggregation.
    • Determine dimensionality and need for slowly changing dimensionality support.
    • Given a scenario, determine the appropriate level of security.

    Data Connectivity (8% of the exam)

    • Given a scenario, determine the data sources and connectors needed.
    • Determine the appropriate method to create connections for data sources.

     

     

    Data Model Design (28% of the exam)

    • Given a scenario, determine the measures and attributes from each data source.
    • Given a scenario, identify the appropriate type of data model.
    • Determine the correct method to optimize the data model for Qlik Sense.
    • Determine the correct method to implement data structures efficiently.

    Data Transformations (38% of the exam)

    • Determine the correct method to build data content based on requirements.
    • Analyze and evaluate null and blank data handling required to support filtering.
    • Determine the correct method to document Data Load scripts.
    • Determine the correct method for date handling techniques.
    • Determine the correct method to perform script organization and cleansing.
    • Analyze relevant variables to build scripts for incremental loading for extract layer.

    Validation (6% of the exam)

    • Given a scenario, determine the appropriate method to validate and test scripts.
    • Given a scenario, determine the appropriate method to validate and test data.

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