Qlik Sense Cookbook - Second Edition

Qlik Sense Cookbook - Second Edition

By : Pablo Labbe, Philip Hand, Neeraj Kharpate

Buy this Book

Qlik Sense Cookbook - Second Edition

By: Pablo Labbe, Philip Hand, Neeraj Kharpate

Buy this Book

Overview of this book

Qlik Sense allows you to explore simple and complex data to reveal hidden insight and data relationships that help you make quality decisions for overall productivity. An expert Qlik Sense user can use its features for business intelligence in an enterprise environment effectively. Qlik Sense Cookbook is an excellent guide for all aspiring Qlik Sense developers and will empower you to create featured desktop applications to obtain daily insights at work. This book takes you through the basics and advanced functions of Qlik Sense February 2018 release. You’ll start with a quick refresher on obtaining data from data files and databases, and move on to some more refined features including visualization, and scripting, as well as managing apps and user interfaces. You will then understand how to work with advanced functions like set analysis and set expressions. As you make your way through this book, you will uncover newly added features in Qlik Sense such as new visualizations, label expressions and colors for dimension and measures. By the end of this book, you will have explored various visualization extensions to create your own interactive dashboard with the required tips and tricks. This will help you overcome challenging situations while developing your applications in Qlik Sense.

Title Page

Packt Upsell

Contributors

Preface

Free Chapter

Getting Started with the Data

Introduction

Extracting data from databases and data files

Extracting data from web files

Extracting data from the FTP server

Extracting data from web services with REST Connector

Activating the legacy mode in Qlik Sense® desktop

Previewing data in the Data model viewer

Creating a master library from the Data model viewer

Using a master library in Edit mode

Using visual data preparation on the data manager model viewer

Visualizations

Introduction

Creating snapshots

Creating and adding content to a story

Adding embedded sheets to the story

Highlighting the performance measure in a bar chart

Associating persistent colors to field values using the script

Using the colormix1 function

Structuring visualizations

Measuring statistical data with box plot charts

Using a waterfall chart to analyze the cumulative effect

Scripting

Introduction

Structuring the script

Efficiently debugging the script

Packaging the code in script files

How to use subroutines in Qlik Sense®

Optimizing the UI calculation speed

Optimizing the reload time of the application

Using a For each loop to load data from multiple files

Using the Concat() function to store multiple field values in a single cell

Executing command-line programs within the script

Managing Apps and the User Interface

Introduction

Publishing a Qlik Sense® application created in Qlik Sense® Desktop

Creating private, approved, and community sheets

Publishing a Qlik Sense® application to Qlik Sense® Cloud

Creating geo maps in Qlik Sense®

Reference lines in a Sales versus Target gauge chart

Effectively using the KPI object in Qlik Sense®

Creating treemaps

Creating dimensionless bar charts in Qlik Sense®

Adding reference lines to trendline charts

Creating text and images

Applying limitations to charts

Adding thumbnails to a clear environment

Navigating many data points in a scatter chart

Using alternative dimensions and measures

Using the visual exploration menu

Useful Functions

Introduction

Using an extended interval match to handle slowly changing dimensions

Using the Previous() function to identify the latest record read for a dimensional value

Using the NetworkDays() function to calculate the working days in a calendar month

Using the Concat() function to display a string of field values as a dimension

Using the Minstring() function to calculate the age of the oldest case in a queue

Using the RangeSum() function to plot cumulative figures in trendline charts

Using the Fractile() function to generate quartiles

Using the FirstSortedValue() function to identify the median in a quartile range

Using the Declare and Derive functions to generate Calendar fields

Setting up a moving annual total figure

Using the For Each loop to extract files from a folder

Using the Peek() function to create a currency exchange rate calendar

Using the Peek() function to create a trial balance sheet

Using the subfield() function to split field into multiple records

Using the dual() function to set the sort order of dimensions

Set Analysis

Introduction

Cracking the syntax for Set Analysis

Using flags in Set Analysis

Using the = sign with variables in Set Analysis

Point in Time using Set Analysis

Using comparison sets in Set Analysis

Using embedded functions in Set Analysis

Creating a multi-measure expression in Set Analysis

Using search strings inside a set modifier

Capturing a list of field values using a Cconcat() function in Set Analysis

Using the element functions P() and E() in Set Analysis

Using the intersection between sets for Basket Analysis

Using alternate states

Using Extensions in Qlik Sense

Introduction

Finding extensions on Qlik Branch

How to import extensions (Desktop and Server)

Using the Variable extension

Using the Reload button extension

Using the simple KPI extension

Using the ShowHide Container extension

Advanced Aggregation with AGGR

Introduction

Using nested aggregations

Using Rank() with Aggr

Combining set analysis with Aggr

Creating an ABC analysis

Tips and Tricks

Introduction

Working with multiple tabs

Using the keyboard to navigate and interact

Working with the distinct clause

Managing variables in the script and layout

Using measure names in object expressions

Creating dynamic charts

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Optimizing the reload time of the application

There are two methods of loading data from QVDs: optimized and non-optimized. The key point here is that the optimized loads can be up to 100 times quicker than the non-optimized loads.

This speed increase is a result of the data passing directly from the disk (QVD) into the memory (RAM) without being unpacked from its compressed QVD format.

As you may have guessed, the reason every load is not optimized is that we often want to change the data coming out of the QVD. This requires it to be uncompressed before going into memory; hence, it is significantly slower. Just about any change to the data will cause the load to be non-optimized; however, there are a few things that we can do.

Getting ready

Open a new QlikSense application and go straight to the Data load editor
Create a folder library connection to any location where you want to save example data files, and call that connectionQVDs

How to do it…

Copy the following code into the Data load editor...

Qlik Sense Cookbook - Second Edition

By : Pablo Labbe, Philip Hand, Neeraj Kharpate

Qlik Sense Cookbook - Second Edition

By: Pablo Labbe, Philip Hand, Neeraj Kharpate

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