Cover image for Hands-On Business Intelligence with Qlik Sense

Hands-On Business Intelligence with Qlik Sense

Author Jerry DiMaso , Kaushik Solanki , Clever Anjos , Pablo Labbe
Release Date: 2019/02/01
ISBN: 9781789800944
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Book Description

Create dynamic dashboards to bring interactive data visualization to your enterprise using Qlik Sense

Key Features

  • Implement various Qlik Sense features to create interactive dashboards
  • Analyze data easily and make business decisions faster using Qlik Sense
  • Perform self-service data analytics and geospatial analytics using an example-based approach

Book Description

Qlik Sense allows you to explore simple-to-complex data to reveal hidden insights and data relationships to make business-driven decisions.

Hands-On Business Intelligence with Qlik Sense begins by helping you get to grips with underlying Qlik concepts and gives you an overview of all Qlik Sense's features. You will learn advanced modeling techniques and learn how to analyze the data loaded using a variety of visualization objects. You'll also be trained on how to share apps through Qlik Sense Enterprise and Qlik Sense Cloud and how to perform aggregation with AGGR. As you progress through the chapters, you'll explore the stories feature to create data-driven presentations and update an existing story. This book will guide you through the GeoAnalytics feature with the geo-mapping object and GeoAnalytics connector. Furthermore, you'll learn about the self-service analytics features and perform data forecasting using advanced analytics. Lastly, you'll deploy Qlik Sense apps for mobile and tablet.

By the end of this book, you will be well-equipped to run successful business intelligence applications using Qlik Sense's functionality, data modeling techniques, and visualization best practices.

What you will learn

  • Discover how to load, reshape, and model data for analysis
  • Apply data visualization practices to create stunning dashboards
  • Make use of Python and R for advanced analytics
  • Perform geo-analysis to create visualizations using native objects
  • Learn how to work with AGGR and data stories

Who this book is for

If you're a data analyst, BI developer, or interested in business intelligence and want to gain practical experience of working on Qlik Sense, this book is for you. You'll also find it useful if you want to explore Qlik Sense's next-generation applications for self-service business intelligence. No prior experience of working with Qlik Sense is required.

Table of Contents

  1. Title Page
  2. Copyright and Credits
    1. Hands-On Business Intelligence with Qlik Sense
  3. About Packt
    1. Why subscribe?
    2. Packt.com
  4. Contributors
    1. About the authors
    2. About the reviewer
    3. Packt is searching for authors like you
  5. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
      1. Download the example code files
      2. Download the color images
      3. Conventions used
    4. Get in touch
      1. Reviews
  6. Section 1: Qlik Sense and Business Intelligence
  7. Getting Started with Qlik Sense
    1. An overview of the Qlik Sense product
      1. The components of Qlik Sense
        1. In-memory associative database
        2. ETL engine
          1. Data manager
          2. Script
          3. Data model
        3. Visualization platform
          1. The hub
          2. Application overview
          3. Sheets
          4. Objects
        4. API and extensibility capabilities
      2. The Associative Engine
      3. Setting up Qlik Sense Desktop
      4. Setting up Qlik Sense Cloud
      5. Self-service with Qlik Sense
    2. Summary
  8. Section 2: Data Loading and Modeling
  9. Loading Data in Qlik Sense
    1. Technical requirements
    2. Data loading process
      1. Loading data from data sources
      2. Data connections
      3. Data manager
        1. Dragging a data file into your application
        2. Loading a data file from a folder (Qlik Sense Desktop)
        3. Loading a data file from data files (QlikCloud)
        4. Creating calculated fields
      4. Data load editor
    3. Table associations
    4. Data profiling
      1. Profiling using the Data manager
      2. Profiling using the Data model viewer
    5. Summary
    6. Further reading
  10. Implementing Data Modeling Techniques
    1. Technical requirements
    2. An overview of data modeling
      1. Data modeling techniques
        1. Entity relationship modeling
        2. Dimensional modeling
    3. Joining
      1. Types of joins
        1. Join/outer join
        2. Left join
        3. Right join
        4. Inner join
      2. Pitfalls of using joins
    4. Concatenation 
      1. Automatic concatenation
      2. Forced concatenation
      3. The NoConcatenate
    5. Filtering
      1. Filtering data using the Data manager
      2. Filtering data in the script editor
    6. QVDs
      1. Why use QVDs?
    7. Link table
    8. Canonical dates
    9. As-Of Table
    10. Script optimization
      1. Using Applymap instead of joins
        1. Applymap()
      2. Reducing the size of data as much as possible
      3. Optimized QVD load
        1. Non-optimized load
        2. Optimized load
      4. Dropping unwanted tables immediately after use
    11. Summary
    12. Sample questions
    13. Further reading
  11. Section 3: Building an Analytical Application
  12. Working with Application Structure
    1. Technical requirements
    2. Application overview
      1. Toolbars
    3. Understanding the DAR methodology
    4. Creating visualization objects
      1. Getting started
      2. Generating visualizations using Insights Advisor
      3. Generating visualizations using Insights Advisor for selected fields
      4. Creating visualizations using chart suggestions
      5. Creating visualizations manually
    5. Creating Master items
      1. Creating master dimensions
      2. Creating master measures
      3. Creating master visualizations
    6. Calculation expressions
    7. Summary
    8. Questions
    9. Further reading
  13. Creating a Sales Analysis App Using Qlik Sense
    1. Technical requirements
    2. Creating the dashboard sheet
      1. Creating the dashboard
        1. Creating a new sheet for the dashboard
        2. Creating KPI visualizations
        3. Creating a pie chart with Sales $ by Categories
        4. Creating a bar chart with Sales $ by Top 10 Customers
        5. Creating the geographical map of sales by country
        6. Creating a filter pane with Order Year and Order Month fields
    3. Creating the analysis sheets
      1. Creating a customer analysis sheet
        1. Creating a new sheet for customer analysis
        2. Adding a filter pane with main dimensions
        3. Adding KPI visualizations
        4. Creating a combo chart for Pareto (80/20) analysis
        5. Creating a table chart with customer information
      2. Creating a product analysis sheet
        1. Creating a new sheet for product analysis
        2. Adding a filter pane
        3. Adding KPI visualizations
        4. Creating a bar chart with a drill-down dimension
        5. Creating a line chart by OrderMonthYear and Category
        6. Creating a scatter plot
    4. Creating a reporting sheet
      1. Creating a new sheet
      2. Adding a default filter pane
    5. Summary
  14. Interacting with Advanced Expressions
    1. Technical requirements
    2. Creating calculations with conditions
      1. Condition to show a text message
      2. Condition to show a different calculation
      3. Condition to filter data on a measure
    3. Using TOTAL for aggregation scope
      1. Calculating the relative share over the total
      2. Calculating the relative share over a dimension
    4. Using some useful inter-record functions
      1. Calculating sales variance year over year
    5. Using AGGR for advanced aggregation
      1. Calculating the top sales product over each category
    6. Leveraging Set Analysis for in-calculation selection
      1. Selecting a specific country for comparison
    7. Summary
    8. Further reading
  15. Creating Data Stories
    1. An overview of stories
    2. Creating snapshots
    3. Planning and organizing your presentation
    4. Creating stories
    5. Editing your story
    6. Sharing stories
    7. Summary
    8. Further reading
  16. Section 4: Additional Features
  17. Engaging On-Demand App Generation
    1. Technical requirements
    2. How Qlik Sense handles large volumes of data 
    3. Setting up a Google BigQuery account
    4. Configuring Qlik Sense for ODAG applications
    5. Building a summarized application
      1. Creating a connection
      2. Adding a script to retrieve data
    6. Building the detailed application
      1. Binding expressions in on-demand template apps
      2. Recovering a long list of selected (or possible) values
      3. Adding restrictions
      4. Creating a dynamic SQL 
    7. Integrating the summarized and detailed applications
      1. Testing our on-demand application
    8. Summary
    9. Further reading
  18. Creating a Native Map Using GeoAnalytics
    1. Technical requirements
    2. Concepts of GeoAnalytics
    3. Creating a map
      1. Loading geographical data
      2. Adding the base map
      3. Adding layers
        1. Area layer
        2. Heatmap layer
    4. Adding more information to the map
      1. Label
      2. Info Bubble
    5. Summary
    6. Further reading
  19. Working with Self-Service Analytics
    1. Technical requirements
    2. Creating self-service analytics
      1. Publishing an application
      2. Creating a new sheet in a published app
    3. Sharing insights with community sheets
    4. Approving sheets to add them to a baseline
    5. Co-creating applications in Qlik Sense Cloud Business
      1. Managing members
      2. Editing the application with multiple users
      3. Sharing the app with users
      4. Publishing changes to a published application
    6. Summary
    7. Further reading
  20. Data Forecasting Using Advanced Analytics
    1. Technical requirements
    2. Qlik Sense Engine and Server Side Extensions
      1. Qlik approach to data science platforms
      2. How SSE works
      3. SSE functions
    3. Preparing your R environment
      1. Installing R
      2. Installing Rserve()
      3. Installing more packages
      4. Installing the SSE plugin
      5. Configuring Qlik Sense
        1. Qlik Sense Desktop
        2. Qlik Sense Enterprise
      6. Starting all services
    4. Using the R extension in a Qlik Sense application
    5. Preparing your Python environment
      1. Installing Python
      2. Updating Python pip
      3. Installing TensorFlow
    6. Using a Python extension
      1. Configuring Qlik Sense
        1. Qlik Sense Desktop
        2. Qlik Sense Enterprise
    7. Using the Python SSE in your apps
    8. Summary
    9. Questions
    10. Further reading
  21. Deploying Qlik Sense Apps for Mobile/Tablets
    1. Technical requirements
    2. Setting up the Sales Analysis app for mobile usage
      1. Responsive layouts
      2. Responsive object design
      3. Reviewing the responsive design of the Sales Analysis application
      4. The Quick view sheet
    3. Choosing the right client
    4. Preparing the Sales Analysis app for offline usage
    5. Summary
  22. Other Books You May Enjoy
    1. Leave a review - let other readers know what you think