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Learning QlikView Data Visualization

Book Description

A complete guide to turning your data into many different chart types using QlikView. Starting with data analysis and progressing to visualization, it’s ideal for anyone who wants to convey information in a clear and graphic way.

  • 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

  • In Detail

    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.

    Table of Contents

    1. Learning QlikView Data Visualization
      1. Table of Contents
      2. Learning QlikView Data Visualization
      3. Credits
      4. Foreword
      5. About the Author
      6. About the Reviewers
      7. www.PacktPub.com
        1. Support files, eBooks, discount offers and more
          1. Why Subscribe?
          2. Free Access for Packt account holders
          3. Instant Updates on New Packt Books
      8. Preface
        1. What this book covers
        2. What you need for this book
        3. Who this book is for
        4. Conventions
        5. Reader feedback
        6. Customer support
          1. Downloading the example code
          2. Errata
          3. Piracy
          4. Questions
      9. 1. First Things First
        1. Project background
        2. People
          1. Ownership
          2. Driven
          3. Honest
          4. Flexible
          5. Analytical
          6. Knowledgeable
          7. Team player
        3. Data
          1. Reliable
          2. Detailed
          3. Formal
          4. Flexible
          5. Referential
        4. Tools
          1. Fast and easy implementation
          2. Business empowerment
          3. Enterprise-ready
        5. QlikView
          1. Installing QlikView
            1. Important general configuration
          2. Let's start discovering data
            1. Opening our first QlikView application
              1. Data model
              2. Metadata
              3. Data preview
              4. Listboxes
              5. Table boxes
        6. Summary
      10. 2. Rank Analysis
        1. What is rank analysis?
        2. Bar chart
          1. Objects to support bar charts
            1. Listbox
            2. Search object
            3. Current selections box
        3. Data visualization style guide for bar charts
          1. Rule 1 – use adequate labeling
            1. Chart labels
            2. Dimension and metric labels
            3. Axes labels
          2. Rule 2 – convert color into data
            1. Associative
            2. Highlighting
              1. Important functions
          3. Alerts
          4. Heat map
          5. Rule 3 – add more detail
            1. Additional dimensions
              1. Grouped bar chart
              2. Stacked bar chart
              3. Trellis chart
            2. Additional expressions
              1. Set analysis
          6. Rule 4 – throw away chartjunk
          7. Rule 5 – respect usability
            1. Caption
              1. Export to Excel
              2. Minimize
              3. Maximize
              4. Copy Image to Clipboard
              5. Fast change
            2. Inside the chart
          8. Rule 6 – be honest
            1. Chart width to height ratio
            2. Axis not forced to zero
        4. Summary
      11. 3. Trend Analysis
        1. What is trend analysis?
        2. The line chart
          1. Objects to support line charts
        3. Data visualization style guide for line charts
          1. Rule 1 – use adequate labeling
            1. Chart labels
            2. Dimension and metric labels
            3. Axes labels
          2. Rule 2 – convert color into data
            1. Associative
            2. Dynamic highlighting
              1. Set analysis
              2. Important functions
            3. References
          3. Rule 3 – add more detail
            1. Additional dimension
              1. Trellis chart
            2. Additional metric
          4. Rule 4 – throw away chartjunk
            1. Axis and grid lines
          5. Rule 5 – respect usability
            1. Caption
            2. Inside the chart
              1. Dimensional group
          6. Rule 6 – being honest
            1. Chart width to height ratio
            2. Axis not forced to zero
        4. Summary
      12. 4. Multivariate Analysis
        1. What is multivariate analysis?
        2. Table charts
          1. Heat map
          2. Mini-charts
            1. Straight table for multiple metrics
              1. Important functions
            2. Pivot table for multiple dimensions
        3. Data visualization style guide for table charts
          1. Rule 1 – use adequate labeling
          2. Chart labels
          3. Dimension and metric labels
          4. Rule 2 – convert color into data
          5. Rule 3 – add more detail
          6. Rule 4 – throw away chartjunk
            1. Number format
            2. Table grid
          7. Rule 5 – respect usability
          8. Rule 6 – be honest
        4. Summary
      13. 5. Distribution Analysis
        1. What is distribution analysis?
        2. Histogram chart
            1. Important functions
              1. Advanced searches in set analysis
          1. The histogram specific properties
          2. Objects to support histogram charts
            1. The input box
        3. Data visualization style guide for histogram charts
          1. Rule 1 – use adequate labeling
            1. Dimensional reference lines
            2. Important functions
          2. Rule 2 – convert color into data
          3. Rule 3 – add more detail
            1. Frequency polygon
            2. Box plot
          4. Rule 4 – throw away chartjunk
          5. Rule 5 – respect usability
          6. Rule 6 – be honest
        4. Summary
      14. 6. Correlation Analysis
        1. What is correlation analysis?
        2. Scatterplot chart
        3. Data visualization style guide for scatterplot charts
          1. Rule 1: use adequate labeling
            1. Trendlines
          2. Rule 2 – convert color into data
            1. Important function
          3. Rule 3 – add more detail
            1. Z axis
            2. Trails
            3. Animation
          4. Rule 4 – throw away chartjunk
          5. Rule 5 – respect usability
          6. Rule 6 – be honest
        4. Summary
      15. 7. Geographical Analysis
        1. What is geographical analysis?
        2. QlikMarket
        3. Area map chart
          1. Dimensions
          2. Metrics
        4. Data visualization style guide for area map charts
          1. Rule 1 – use adequate labeling
          2. Rule 2 – convert color into data
          3. Rule 3 – add more detail
          4. Rule 4 – throw away chartjunk
          5. Rule 5 – respect usability
          6. Rule 6 – be honest
        5. Summary
      16. 8. What-if Analysis
        1. What is what-if analysis?
        2. Global variable what-if analysis
          1. Global variables
        3. Detailed variable what-if analysis
          1. Detailed variables
        4. Summary
      17. 9. Dashboards and Navigation
        1. What is a dashboard?
        2. The dashboard application
          1. Document settings
          2. Variables
          3. Layout
          4. Supporting objects
          5. Lines
          6. Text objects for images
          7. Current selections box
          8. The search object
          9. The loaded listboxes
            1. Important functions
          10. Multibox
          11. The bookmark object
          12. Arranging objects
          13. Listboxes for dates
        3. Key Performance Indicators (KPI's)
          1. Icons
          2. Quick global perspective
          3. The gauge chart
          4. KPI breakdown
            1. The KPI table
              1. Visual cues
              2. Alert images
              3. The mini-charts
          5. Brief analysis
            1. Migration
            2. The container object
            3. Buttons and actions
        4. Summary
      18. Index