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Updated in [October 18th, 2023]
What does this course tell?
(Please note that the following overview content is from the original platform)
Take the first steps to becoming a data visualisation engineer
Fully downloadable content for offline viewing (Copyright applies)
Identify KPIsmetrics and dimensions from your business requirements
Design and build data visualisations and enhance them with extensions
Understand the associative model and how to load data to it
Resolve data integrity and modelling issues
Code expressions for metrics and dimensions
Source code for all apps used in course creation
Will have hands on experience
Develop and share apps in the cloud (for free)
We considered the value of this course from many aspects, and finally summarized it for you from two aspects: skills and knowledge, and the people who benefit from it:
(Please note that our content is optimized through artificial intelligence tools and carefully reviewed by our editorial staff.)
What skills and knowledge will you acquire during this course?
During the Certificate in Qlik Sense Analytics Development course, the learner will acquire the following skills and knowledge:
1. Identifying KPIs, metrics, and dimensions based on business requirements.
2. Designing and building data visualizations using Qlik Sense.
3. Enhancing data visualizations with extensions.
4. Understanding the associative model and how to load data into it.
5. Resolving data integrity and modeling issues.
6. Coding expressions for metrics and dimensions.
7. Gaining hands-on experience through practical exercises.
8. Accessing the source code for all apps used in the course creation.
9. Developing and sharing apps in the cloud for free.
By completing this course, the learner will be equipped with the necessary skills to begin a career as a data visualization engineer.
Who will benefit from this course?
This course will benefit individuals interested in becoming data visualization engineers. It is also suitable for professionals in fields such as business intelligence, data analysis, and data science.
