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Data Analytics using Qlik Sense Course Overview

Data Analytics using Qlik Sense Course Overview

The Data Analytics using Qlik Sense course is a comprehensive learning path designed for individuals seeking expertise in Qlik Sense for performing data analytics. By delving into this course, learners will gain a robust understanding of how Qlik Sense stands out from QlikView and the significance of self-service BI tools. They will explore its intuitive interface for creating dynamic dashboards and reports along with practical skills such as data modeling, Creating data architectures, and mastering advanced data modeling techniques.

Furthermore, the course covers Qlik Sense's enterprise capabilities, Visualization tools, Set analysis, and Advanced chart creation. Learners will also familiarize themselves with the Master Library, the art of Data storytelling, and extending Qlik Sense's functionality through Mashups and extensions. Security aspects form an essential component of the curriculum, ensuring users understand how to manage content security and implement security rules effectively.

Armed with the knowledge from this course, learners will excel in harnessing Qlik Sense for insightful data discovery, Visual analytics, and collaboration among team members, thereby enhancing their data-driven decision-making capabilities in the business landscape.

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Course Prerequisites

To ensure that you can successfully undertake the Data Analytics using Qlik Sense course and gain the most from it, the following are the minimum required prerequisites:


  • Basic Understanding of Data Concepts: Familiarity with the basic concepts of data and its importance in business decision-making.
  • Familiarity with Business Intelligence: An understanding of what business intelligence (BI) is and why it is beneficial to organizations.
  • Interest in Data Visualization: A keen interest in visualizing data and extracting insights from visual representations.
  • Elementary Computer Literacy: Competence in using a computer, managing files, and navigating through software interfaces.
  • Basic Knowledge of Data Handling: Understanding of how data can be sourced, manipulated, and organized for analysis.
  • Problem-Solving Skills: An analytical mindset and the ability to think critically to solve problems using data.
  • Willingness to Learn: A readiness to engage with new tools and concepts related to data analytics and visualization.

No prior experience with Qlik Sense or QlikView is required, as the course will cover the necessary foundations of these tools. However, those with experience in other BI tools or data analytics may find it easier to grasp the concepts introduced in the course.


Target Audience for Data Analytics using Qlik Sense

Koenig Solutions' Data Analytics using Qlik Sense course is designed for professionals seeking expertise in dynamic data visualization and analytics.


  • Data Analysts
  • Business Intelligence Professionals
  • Business Analysts
  • Data Science Enthusiasts
  • IT Analysts
  • BI Developers
  • Reporting Professionals
  • Data Visualization Specialists
  • Project Managers overseeing BI tasks
  • Professionals looking to transition into data-centric roles
  • QlikView Developers upgrading to Qlik Sense
  • System Administrators managing BI tools
  • Database Professionals aiming to enhance their reporting skills
  • Product Managers requiring analytics for product performance tracking
  • Marketing Managers needing insights from customer data
  • Financial Analysts seeking advanced reporting tools
  • Quality Assurance Specialists involved in data validation and visualization
  • Data Architects
  • Students pursuing a career in data analytics or business intelligence


Learning Objectives - What you will Learn in this Data Analytics using Qlik Sense?

Introduction to Learning Outcomes:

The Data Analytics using Qlik Sense course equips learners with comprehensive skills in data visualization, modeling, and analytics to create insightful dashboards and reports using Qlik Sense tools.

Learning Objectives and Outcomes:

  • Understand the differences between Qlik Sense and QlikView and the importance of self-service BI tools.
  • Master the drag-and-drop visualization features and the Qlik Data indexing engine for effective data handling.
  • Learn data modeling best practices to efficiently transform and relate data within Qlik Sense.
  • Develop ability to create a robust data architecture, including conversion of QlikView files and managing synthetic keys and circular references.
  • Gain expertise in advanced data modeling techniques, such as using star schema, link tables, and creating optimized data models.
  • Explore Qlik Sense Enterprise tools for rapid app development, Big Data integration, and maintaining enterprise security.
  • Create compelling visualizations with Qlik Sense charts, maps, and storytelling features for enhanced data presentations.
  • Acquire skills in set analysis for complex comparative and point-in-time analyses to extract deeper insights.
  • Learn to build and test mashups and extensions to extend Qlik Sense capabilities and create custom visual experiences.
  • Understand security mechanisms within Qlik Sense, including content security, security rules, and dynamic data reduction strategies.

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