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.
Table of Contents (18 chapters)
Free Chapter
1
Section 1: Qlik Sense and Business Intelligence
3
Section 2: Data Loading and Modeling
6
Section 3: Building an Analytical Application
11
Section 4: Additional Features

Using the Python SSE in your apps

Now that the Python environment is all set, we can use the functions we've enabled to allow linear regressions to analyze the data on the default data model.

Start by adding a line graph to your app. Use the Order Week as a dimension and add Sum(SalesAmmount) as a measure; check if you get an output.

Post this and add a linear regression line. Please add another measure with Linear.simple ([OrderDate.autoCalendar.Week],sum(SalesAmmount)) as an expression.

The red line is calculated using our Python module, returning the values for our simple method.

When we've downloaded the GitHub package, there's a file named DataTrends.qvf. Please import this into Qlik Sense and check the examples for the other two methods. In this screen, you can compare linear regression using native Qlik functions and the three methods (Simple Linear, Linear...