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

Summary

In this chapter, we were able to learn that Qlik is capable of exchanging data with external platforms, enabling some calculations to be made for modern data science tools. We've also learned how to install the necessary software and make adjustments to the Qlik Sense box to connect to various platforms.

In addition to this, we've created some analysis for our Qlik Sense applications that can use R and/or Python, leveraging the user's experience with time-series analysis.

In the next chapter, we are going to see how to deploy Qlik Sense apps for mobile devices.