Labbe P., et al. / Лаббе П., и др. - Hands-On Business Intelligence with Qlik Sense / Практическая бизнес-аналитика с Qlik Sense [2019, PDF, ENG]

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Preface 1
Section 1: Qlik Sense and Business Intelligence
Chapter 1: Getting Started with Qlik Sense 8
An overview of the Qlik Sense product 9
The components of Qlik Sense 9
In-memory associative database 10
ETL engine 10
Data manager 10
Script 11
Data model 11
Visualization platform 13
The hub 13
Application overview 14
Sheets 15
Objects 16
API and extensibility capabilities 17
The Associative Engine 18
Setting up Qlik Sense Desktop 22
Setting up Qlik Sense Cloud 24
Self-service with Qlik Sense 26
Summary 33
Section 2: Data Loading and Modeling
Chapter 2: Loading Data in Qlik Sense 35
Technical requirements 35
Data loading process 36
Loading data from data sources 37
Data connections 38
Data manager 38
Dragging a data file into your application 38
Loading a data file from a folder (Qlik Sense Desktop) 41
Loading a data file from data files (QlikCloud) 45
Creating calculated fields 49
Data load editor 57
Table associations 59
Data profiling 63
Profiling using the Data manager 64
Profiling using the Data model viewer 67
Summary 73Table of Contents
[ ii ]
Further reading 73
Chapter 3: Implementing Data Modeling Techniques 74
Technical requirements 75
An overview of data modeling 75
Data modeling techniques 77
Entity relationship modeling 77
Dimensional modeling 79
Joining 83
Types of joins 84
Join/outer join 85
Left join 87
Right join 88
Inner join 90
Pitfalls of using joins 91
Concatenation 92
Automatic concatenation 92
Forced concatenation 94
The NoConcatenate 95
Filtering 96
Filtering data using the Data manager 96
Filtering data in the script editor 97
QVDs 99
Why use QVDs? 99
Link table 101
Canonical dates 104
As-Of Table 108
Script optimization 112
Using Applymap instead of joins 113
Applymap() 113
Reducing the size of data as much as possible 115
Optimized QVD load 115
Non-optimized load 116
Optimized load 116
Dropping unwanted tables immediately after use 118
Summary 118
Sample questions 119
Further reading 119
Section 3: Building an Analytical Application
Chapter 4: Working with Application Structure 121
Technical requirements 121
Application overview 122
Toolbars 123
Understanding the DAR methodology 124Table of Contents
[ iii ]
Creating visualization objects 127
Getting started 128
Generating visualizations using Insights Advisor 130
Generating visualizations using Insights Advisor for selected fields 134
Creating visualizations using chart suggestions 138
Creating visualizations manually 148
Creating Master items 155
Creating master dimensions 155
Creating master measures 157
Creating master visualizations 159
Calculation expressions 160
Summary 161
Questions 162
Further reading 162
Chapter 5: Creating a Sales Analysis App Using Qlik Sense 163
Technical requirements 164
Creating the dashboard sheet 164
Creating the dashboard 165
Creating a new sheet for the dashboard 165
Creating KPI visualizations 166
Creating a pie chart with Sales $ by Categories 171
Creating a bar chart with Sales $ by Top 10 Customers 176
Creating the geographical map of sales by country 181
Creating a filter pane with Order Year and Order Month fields 189
Creating the analysis sheets 192
Creating a customer analysis sheet 193
Creating a new sheet for customer analysis 193
Adding a filter pane with main dimensions 194
Adding KPI visualizations 199
Creating a combo chart for Pareto (80/20) analysis 201
Creating a table chart with customer information 209
Creating a product analysis sheet 212
Creating a new sheet for product analysis 213
Adding a filter pane 213
Adding KPI visualizations 215
Creating a bar chart with a drill-down dimension 219
Creating a line chart by OrderMonthYear and Category 224
Creating a scatter plot 227
Creating a reporting sheet 229
Creating a new sheet 230
Adding a default filter pane 230
Summary 232
Chapter 6: Interacting with Advanced Expressions 233
Technical requirements 233
Creating calculations with conditions 234Table of Contents
[ iv ]
Condition to show a text message 234
Condition to show a different calculation 239
Condition to filter data on a measure 243
Using TOTAL for aggregation scope 247
Calculating the relative share over the total 248
Calculating the relative share over a dimension 251
Using some useful inter-record functions 254
Calculating sales variance year over year 255
Using AGGR for advanced aggregation 257
Calculating the top sales product over each category 258
Leveraging Set Analysis for in-calculation selection 260
Selecting a specific country for comparison 262
Summary 266
Further reading 266
Chapter 7: Creating Data Stories 267
An overview of stories 268
Creating snapshots 269
Planning and organizing your presentation 271
Creating stories 272
Editing your story 280
Sharing stories 290
Summary 292
Further reading 292
Section 4: Additional Features
Chapter 8: Engaging On-Demand App Generation 294
Technical requirements 295
How Qlik Sense handles large volumes of data 295
Setting up a Google BigQuery account 299
Configuring Qlik Sense for ODAG applications 303
Building a summarized application 305
Creating a connection 305
Adding a script to retrieve data 309
Building the detailed application 311
Binding expressions in on-demand template apps 311
Recovering a long list of selected (or possible) values 312
Adding restrictions 313
Creating a dynamic SQL 313
Integrating the summarized and detailed applications 315
Testing our on-demand application 319
Summary 323
Further reading 323Table of Contents
[ v ]
Chapter 9: Creating a Native Map Using GeoAnalytics 324
Technical requirements 324
Concepts of GeoAnalytics 325
Creating a map 327
Loading geographical data 327
Adding the base map 329
Adding layers 332
Area layer 332
Heatmap layer 338
Adding more information to the map 341
Label 342
Info Bubble 343
Summary 344
Further reading 344
Chapter 10: Working with Self-Service Analytics 345
Technical requirements 346
Creating self-service analytics 346
Publishing an application 347
Creating a new sheet in a published app 347
Sharing insights with community sheets 355
Approving sheets to add them to a baseline 357
Co-creating applications in Qlik Sense Cloud Business 359
Managing members 361
Editing the application with multiple users 362
Sharing the app with users 363
Publishing changes to a published application 364
Summary 365
Further reading 365
Chapter 11: Data Forecasting Using Advanced Analytics 366
Technical requirements 367
Qlik Sense Engine and Server Side Extensions 367
Qlik approach to data science platforms 367
How SSE works 368
SSE functions 369
Preparing your R environment 370
Installing R 370
Installing Rserve() 376
Installing more packages 378
Installing the SSE plugin 379
Configuring Qlik Sense 379
Qlik Sense Desktop 379
Qlik Sense Enterprise 380
Starting all services 381Table of Contents
[ vi ]
Using the R extension in a Qlik Sense application 382
Preparing your Python environment 386
Installing Python 387
Updating Python pip 389
Installing TensorFlow 389
Using a Python extension 390
Configuring Qlik Sense 390
Qlik Sense Desktop 391
Qlik Sense Enterprise 391
Using the Python SSE in your apps 392
Summary 392
Questions 393
Further reading 393
Chapter 12: Deploying Qlik Sense Apps for Mobile/Tablets 394
Technical requirements 395
Setting up the Sales Analysis app for mobile usage 395
Responsive layouts 396
Responsive object design 397
Reviewing the responsive design of the Sales Analysis application 399
The Quick view sheet 403
Choosing the right client 409
Preparing the Sales Analysis app for offline usage 410
Summary 411
Other Books You May Enjoy 412
Index 415