NTUC LearningHub

This course will provide learners with the necessary skills to develop a coherent data model in Qlik Sense by loading and transforming multiple data sources as well as to optimize query with Set Analysis and resolving data model issues. With information, tools, techniques, and exercises, this course includes topics dealing with maintaining data connections, cleansing and transforming source data, architecting data models. Optimising for performance and application development on Qlik Sense.

 

Course Objectives

 

  • Utilise data modelling tools and techniques to create data models to deliver business value
  • Use the Data Load Editor and the Data Manager effectively and efficiently for data transformation and optimisation to portray trends and findings
  • Resolve data modelling issues such as synthetic keys and circular references for the presentation of data to portray critical trends and patterns
  • Generate data using techniques for better dashboard visualisation and performance
  • Combine tables to customize data requirements from the data model to enable better analytics capabilities
  • Handle advanced modelling challenges for the mapping of data for better data displays to address the questions of stakeholders
  • Apply concepts to develop and debug data scripts from the data model to suit the data visualisations
  • Use the Set Analysis to optimize data queries for data visualisations with display features to align interpretation and presentation of data analytics findings
  • Work with server, data and object security for performance considerations with considerations for good user experience and strategic visualisations

 

Pre-requisites

 

The admission requirements are:

  • Creating Visualizations with Qlik Sense (advantageous)
  • Database and SQL query knowledge
  • Read, write, and speak English at WPL Level 4
  • Manipulate numbers at WPN Level 4
  • Hardware & Software
    • This course will be conducted as a Virtual Live Class (VLC) via Zoom platform
    • Participants must own a Zoom account and have a laptop or a desktop with “Zoom Client for Meetings” installed. Download from zoom.us/download.

System Requirement

Must-have:
Please ensure that your computer or laptop meets the following requirements.

  • Operating system: Windows 10 or MacOS (64 bit or above)
  • Processor/CPU: 1.8 GHz, 2-core Intel Core i3 or higher
  • Minimum 20 GB hard disk space
  • Minimum 8 GB RAM
  • Webcam (camera must be turned on for the duration of the class)
  • Microphone
  • Internet Connection: Wired or Wireless broadband
  • Latest version of Zoom software to be installed on computer or laptop prior to the class.

Good-to-have:

  • Wired internet connection
    Wired internet will provide you with stable and reliable connection.
  • Dual monitors
    Using a dual monitor setup will undoubtedly improve your training experience, enabling you to simultaneously participate in hands-on exercises and maintain engagement with your instructor.

Not recommended:
Using tablets are not recommended due to their smaller screen size, which could cause eye strain and discomfort over the course of the program's duration.

 

Course Outline

 

Module 1: Modelling Data With Qlik Sense

  • Qlik Sense deployment architecture
  • Data sources and data structures
  • Qlik Sense Platform and Qlik Sense App
  • Create a new app
  • Data load editor and script sections

 

Module 2: Sourcing & Loading Data

  • Data connections
  • Extract data from a database
  • Data model viewer
  • Loading file data

 

Module 3: Resolving Common Modelling Issues

  • Synthetic keys
  • Counting table records
  • Circular references
  • Basic data transformations

 

Module 4: Generating Data

  • Adding Calculated Fields to a table
  • Limiting and re-using data
  • Creating composite keys
  • Master calendar

 

Module 5: Combining Data

  • Mapping Table
  • Preceding load on preceding load
  • Joining Tables
  • Concatenation

 

Module 6: Handling Advanced Modelling Challenges

  • Aggregation Tables
  • Cross Tables
  • Link Tables
  • Data Classification

 

Module 7: Developing and Debugging

  • Control script execution
  • Reusing script
  • Script variables
  • Debugging scripts

 

Module 8: Applying Finishing Touches

  • Defining and Working With Data Sets in Expressions
  • Aggregation Functions
  • Reusable Items and Object Library
  • Data Islands
  • QVD Files
  • Performance Considerations

 

Module 9: Exploring Security and Advance Concepts

  • Big Data with Qlik Sense
  • Managing Security with Section Access
  • Profiling Data
  • Reloading from the Hub
  • Evaluating App Performance
  • Advance Analytics Integration in Qlik Sense

 

Certificate Obtained and Conferred by

 

  • Upon meeting 75% attendance and passing the assessment, participants will be awarded with a digital Statement of Attainment (SOA), accredited by SkillsFuture Singapore. SOA will be reflected as [ICT-DIT-4006-1.1 Data Visualisation].
  • Upon meeting 75% attendance and passing the assessment, participants will be awarded with a digital Certificate of Completion from NTUC LearningHub.
  • External Certification Exams
    This course prepares trainees for the Qlik Sense Data Architect Certification exam. Upon passing the exam, the participants will receive Qlik Sense Data Architect certification.
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