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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Extracting data from databases and data files

The data within an organization is usually stored in relational databases and data files. Extracting data is the first step toward creating a data model. This section demonstrates the steps to extract data from an MS Access database and a delimited (.CSV) file. The procedure to extract data from other relational databases is the same as the process for extracting data from MS Access.

The dataset that we will use is available publicly and covers information about routes and fares for various transport systems in Hong Kong. The original data files have been downloaded from the https://data.gov.hk/ website. This dataset can also be obtained from the Packt Publishing website.

The data connections in the Qlik Sense Data load editor save shortcuts leading to commonly used data sources, such as databases and data files. The following types of connections exist in Qlik Sense:

ODBC database connection
OLE DB database connection
Folder connection
Web file connection
Qlik Essbase Connector
Qlik ODBC Connector Package
Qlik REST Connector
Qlik Salesforce Connector
Qlik GeoAnalytics Connector
Web Storage Provider Connector

This recipe deals with the ODBC, OLE DB, and Folder connections. The web file connection and REST Connector will be dealt with in a separate recipe.

For the following connections, here is a short description, but we don't have recipes for them in this book:

Qlik Essbase Connector allows data extraction from Hyperion Essbase cubes
Qlik ODBC Connector Package allows data-extraction from several data sources, such as Google Big Query, Amazon Redshift, Hive, Cloudera Impala, IBM DB2, MS SQL Server, My SQL Enterprise Edition, Oracle, PostgreSQL, Sybase ASE, and Teradata

Qlik Salesforce Connector allows data extraction from Salesforce reports with SOAP or the Bulk API
Qlik GeoAnalytics Connector is a new service to make geo-analytics calculations, such as calculating the distance between points, clusters, and merging shapes
Web Storage Provider Connector allows a connection to storage services, such as DropBox, to retrieve data from files, such as XlSX or CSV

With the exception of Qlik GeoAnalytics Connector, all connectors are free to use. GeoAnalytics Connector requires the purchase or subscription of a separate license from Qlik.

Getting ready

The dataset required for this recipe that is downloaded from the Packt Publishing website (https://www.packtpub.com/big-data-and-business-intelligence/qlik-sense-cookbook-second-edition) comes in a zipped folder called QlikSenseData. Extract all the files from this zipped folder and save them on your hard drive at the desired location.

If you are connecting to the database using Open Database Connectivity (ODBC):

Install the relevant ODBC drivers on your system.

Note

For the sake of this exercise, we need the MS Access drivers. The system DSN connection can be set up through the ODBC administrator under Administrative Tools in Control Panel.

While setting up the ODBC connection, select the ROUTE_BUS.mdb file as the data source from the QlikSenseData folder.
Name the ODBC DSN connection as HongKong Buses.
Create a new Qlik Sense application and open the Data load editor.
Click on the Create New Connection and select ODBC.
Select HongKong Buses under System DSN.

Name the data connection as Qlik Sense CookBook ODBC.
The following screenshot shows the details we enter in the Create new connection (ODBC) window:

If you are connecting to the database using OLE DB connectivity, we can directly set this up through the editor:

Open the Data load editor in Qlik Sense.
Click on the Create new connection and select OLE DB.
Select the Microsoft Jet 4.0 OLE DB Provider (32-bit) driver from the provider drop-down list.
Insert the Data Source file path, which, in our case, will be the path for theROUTE_BUS.mdb file in the QlikSenseData folder.
Name the data connection as QlikSense CookBook OLE DB.
The following screenshot shows the details we enter in the Create new connection (OLE DB)window:

If you are extracting the data from a data file, such as .CSV, perform the following steps:

Open the Data load editor in Qlik Sense.
Click on Create new connectionand select Folder.
Select the location of the QlikSenseData folder, which contains our data files. Alternatively, you can enter the path of the source folder directly under Path.
Name the data connection as Qlik Sense CookBook Data.

The following screenshot shows the details we enter in the Create new connection (folder) window:

Once the connections are created in the Qlik Sense library, they will be seen as a list under Data connections in the Data load editor, as shown in the following screenshot:

How to do it…

If you are working with an ODBC or an OLE DB data connection, follow these steps:

Insert the relevant data connection string to the script by clicking on Insert connection string, as shown in the following screenshot:

Click on Select data under Data connections to view and extract data from the ROUTE table in the MS Access database, as shown:

The preview of the ROUTE_BUS.mdb table will look like the following. The fields in the table can be excluded or renamed while working in the Preview window:

Click on Insert script in the Preview window. This will insert the connection string as well as load the statement to the script. Make sure that you delete the duplicate LIB CONNECT TO 'Qlik Sense CookBook ODBC'; statement from your script.
Load the data in your application by clicking on the button.

Keep the Close when successfully finished option checked in the data load progress window. If the data is loaded successfully, the window automatically closes or else the error encountered is highlighted.

On a similar note, in order to test the Qlik Sense data files:

Click on the Select data option under the Qlik Sense CookBook Data connection.
Select the ROUTE_GMB.csv file from the QlikSenseData folder and load it in the application.
The preview of the ROUTE_GMB.csv table will look like the following screenshot. Make sure that you select Embedded field names under Field names. Note that the Delimiter, in this case, is automatically set to Comma:

Insert the script and then save and load it.

How it works…

The LIB CONNECT TO statement connects to a database using a stored data connection from the Qlik Sense library, thus acting as a bridge between our application and the data source.

There's more…

This recipe aimed to extract data from common data sources, such as RDBMSes and data files. Qlik Sense can also extract data from web files and web services. We will see this in the next section.

Qlik Sense Cookbook - Second Edition

By : Pablo Labbe, Philip Hand, Neeraj Kharpate

Qlik Sense Cookbook - Second Edition

By: Pablo Labbe, Philip Hand, Neeraj Kharpate

Overview of this book

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Qlik Sense Cookbook - Second Edition

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Getting ready

Note

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