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

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
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Index