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Certification Path for QSBA2018: Qlik Sense Business Analyst Certification
The exam does not have any certificate pre-requisite but demands the following before a candidate can sit for an exam:
- Understand the QVD layer and architecture of the Qlik platform
- Ability to write Qlik Sense LOAD scripts and validate data
- Ability to architect data to provide optimal performance
- Familiar with SQL and relational databases
- Create and use connectors to various data sources
- Practical experience developing multiple production-quality applications in Qlik Sense
- Basic understanding of Extract-Transform-Load (ETL)
Understanding functional and technical aspects of QSBA2018: Qlik Sense Business Analyst Certification Design Application
The following will be discussed in QLIKVIEW QSBA2018 exam dumps:
- Design the order of the sheets in an application to provide an overall flow matching the expectations of the user journey (DAR concept)
- Based on the business requirements and desired insight, determine the optimal number of charts, correct chart type, order of dimensions, use of color, and measures
- Identify the proper expression to create the appropriate visualization to meet the business requirements
- Leverage appropriate method for data comparisons (filters, bookmarks, alternate states, set analysis)
- Explain the impact of using mobiles devices on app design
- Select object types appropriate for the required data analysis (e.g., a line chart to show a trend over time)
- Distinguish between situations when data security requirements need to use section access or security rules
- Understand when and why to use an alternate chart recommendation
Exam Topics for QSBA2018: Qlik Sense Business Analyst Certification
The following will be discussed in QLIKVIEW QSBA2018 exam dumps:
- Identify Requirements
- Design Application
- Develop Application
- Prepare and Load Data
Qlik QSBA2018 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Storytelling and Sharing | 10% | - Sharing insights and apps
|
| Expressions and Calculations | 20% | - Set Analysis and expressions
|
| Data Modeling | 25% | - Understanding data associations
|
| Data Visualization and App Design | 25% | - Creating and configuring visualizations
|
| Data Loading and Transformation | 20% | - Load Editor usage
|





