Hands-On Business Intelligence with Qlik Sense: Implement self-service data analytics with insights and guidance from Qlik Sense experts

✍ Scribed by Pablo Labbe, Clever Anjos, Kaushik Solanki, Jerry DiMaso

• Publisher: Packt Publishing
• Year: 2019
• Tongue: English
• Leaves: 433
• Category: Library

✦ Synopsis

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. Getting started with Qlik Sense
2. Loading Data in Qlik Sense
3. Implementing Data Modeling Techniques
4. Working with Application Structure
5. Creating a Sales Analysis App using Qlik Sense
6. Interacting with Advanced Expressions
7. Creating Data Stories
8. Engaging ODAG
9. Creating a Native Map Using Geo Analytics
10. Working with Self Service Analytics
11. Data Forecasting Using Advanced Analytics
12. Deploying Qlik Sense Apps for Mobile/Tablets

✦ Table of Contents

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