Book Image

Hands-On Business Intelligence with Qlik Sense

By : Pablo Labbe, Clever Anjos, Kaushik Solanki, Jerry DiMaso
Book Image

Hands-On Business Intelligence with Qlik Sense

By: Pablo Labbe, Clever Anjos, Kaushik Solanki, Jerry DiMaso

Overview of this book

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.

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Table of Contents (18 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Section 1: Qlik Sense and Business Intelligence
Section 1: Qlik Sense and Business Intelligence
2
Getting Started with Qlik Sense
Getting Started with Qlik Sense
An overview of the Qlik Sense product
Summary
3
Section 2: Data Loading and Modeling
Section 2: Data Loading and Modeling
4
Loading Data in Qlik Sense
Loading Data in Qlik Sense
Technical requirements
Data loading process
Table associations
Data profiling
Summary
Further reading
5
Implementing Data Modeling Techniques
Implementing Data Modeling Techniques
Technical requirements
An overview of data modeling
Joining
Concatenation
Filtering
QVDs
Link table
Canonical dates
As-Of Table
Script optimization
Summary
Sample questions
Further reading
6
Section 3: Building an Analytical Application
Section 3: Building an Analytical Application
7
Working with Application Structure
Working with Application Structure
Technical requirements
Application overview
Understanding the DAR methodology
Creating visualization objects
Creating Master items
Calculation expressions
Summary
Questions
Further reading
8
Creating a Sales Analysis App Using Qlik Sense
Creating a Sales Analysis App Using Qlik Sense
Technical requirements
Creating the dashboard sheet
Creating the analysis sheets
Creating a reporting sheet
Summary
9
Interacting with Advanced Expressions
Interacting with Advanced Expressions
Technical requirements
Creating calculations with conditions
Using TOTAL for aggregation scope
Using some useful inter-record functions
Using AGGR for advanced aggregation
Leveraging Set Analysis for in-calculation selection
Summary
Further reading
10
Creating Data Stories
Creating Data Stories
An overview of stories
Creating snapshots
Planning and organizing your presentation
Creating stories
Editing your story
Sharing stories
Summary
Further reading
11
Section 4: Additional Features
Section 4: Additional Features
12
Engaging On-Demand App Generation
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
Building the detailed application
Integrating the summarized and detailed applications
Summary
Further reading
13
Creating a Native Map Using GeoAnalytics
Creating a Native Map Using GeoAnalytics
Technical requirements
Concepts of GeoAnalytics
Creating a map
Adding more information to the map
Summary
Further reading
14
Working with Self-Service Analytics
Working with Self-Service Analytics
Technical requirements
Creating self-service analytics
Sharing insights with community sheets
Approving sheets to add them to a baseline
Co-creating applications in Qlik Sense Cloud Business
Summary
Further reading
15
Data Forecasting Using Advanced Analytics
Data Forecasting Using Advanced Analytics
Technical requirements
Qlik Sense Engine and Server Side Extensions
Preparing your R environment
Using the R extension in a Qlik Sense application
Preparing your Python environment
Using a Python extension
Using the Python SSE in your apps
Summary
Questions
Further reading
16
Deploying Qlik Sense Apps for Mobile/Tablets
Deploying Qlik Sense Apps for Mobile/Tablets
Technical requirements
Setting up the Sales Analysis app for mobile usage
Choosing the right client
Preparing the Sales Analysis app for offline usage
Summary
17
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Creating a Sales Analysis App Using Qlik Sense

In this chapter, we will create a sales analysis application to explore and analyze the data model that we created in Chapter 2, Loading Data in Qlik Sense.

While developing the application, we will apply the Dashboard, Analysis, Reporting (DAR) methodology that we explained in Chapter 4, Working with Application Structures.

We will create create four sheets, each with a very specific purpose, as follows:

  • The dashboard sheet will give us a quick overview of the key performance indicators of sales amounts, average discount percentages, and the number of orders. It will also show us the sales share by category, the sales by top 10 customers, and a map showing the sales statistics for each country.
  • The customer analysis sheet will help our users to understand how the sales are performing based on the customer, and which customers are...
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