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  • Define the characteristics of the people, data, and tools involved in a data discovery project
  • Perform data discovery that helps you validate data quality
  • Understand and execute rank, trend, multivariate, distribution, correlation, geographical, and what-if analysis
  • Create bar, line, scatterplot, heat map, table, histogram, box plot, and geographical charts
  • Prevent data visualization manipulation and the formulation of incorrect conclusions
  • Create a dashboard to present your case and monitor future actions
  • Eliminate non-data and non-usability ink for a clean display
  • Pack more detail into each chart with techniques to add animation, trails, and sparklines, along with creating a trellis chart

While QlikView’s data engine complements our thought processes and gives us the ability to rapidly implement insightful data discovery, we must also learn to use proper analytical and data visualization techniques to enhance our ability to make data more presentable.

Learning QlikView Data Visualization presents a simple way to organize your QlikView data discovery process. Within the context of a real-world scenario and accompanying exercises, you will learn a set of analytical techniques and data visualization best practices that you can customize and apply to your own organization.

We start our data discovery project by reviewing the data, people, and tools involved. We then go on to use rank, trend, multivariate, distribution, correlation, geographical, and what-if analysis as we try to resolve the problems of QDataViz, Inc, a fictitious company used as an example. In each type of analysis, we employ highlighting, heat maps, and other techniques on top of multiple chart types. Once we have a possible solution, we present our case in a dashboard and use performance indicators to monitor future actions.

You will learn how to properly create insightful data visualization in QlikView that covers multiple analytical techniques. By reusing what you’ve learned in Learning QlikView Data Visualization, your organization’s future data discovery projects will be more effective.

  • Explore the basics of data discovery with QlikView
  • Perform rank, trend, multivariate, distribution, correlation, geographical, and what-if analysis
  • Deploy data visualization best practices for bar, line, scatterplot, heat map, tables, histogram, box plot, and geographical charts
  • Communicate and monitor data using a dashboard
Page Count 156
Course Length 4 hours 40 minutes
ISBN 9781782179894
Date Of Publication 24 Sep 2013


Karl Pover

Karl Pover is the owner and principal consultant of Evolution Consulting, which provides QlikView consulting services throughout Mexico. Since 2006, he has been dedicated to providing QlikView presales, implementation, and training for more than 50 customers. He is the author of Learning QlikView Data Visualization, and he has also been a Qlik Luminary since 2014.