Book Image

Machine Learning with Qlik Sense

By : Hannu Ranta
Book Image

Machine Learning with Qlik Sense

By: Hannu Ranta

Overview of this book

The ability to forecast future trends through data prediction, coupled with the integration of ML and AI, has become indispensable to global enterprises. Qlik, with its extensive machine learning capabilities, stands out as a leading analytics platform enabling businesses to achieve exhaustive comprehension of their data. This book helps you maximize these capabilities by using hands-on illustrations to improve your ability to make data-driven decisions. You’ll begin by cultivating an understanding of machine learning concepts and algorithms, and build a foundation that paves the way for subsequent chapters. The book then helps you navigate through the process of framing machine learning challenges and validating model performance. Through the lens of Qlik Sense, you'll explore data preprocessing and analysis techniques, as well as find out how to translate these techniques into pragmatic machine learning solutions. The concluding chapters will help you get to grips with advanced data visualization methods to facilitate a clearer presentation of findings, complemented by an array of real-world instances to bolster your skillset. By the end of this book, you’ll have mastered the art of machine learning using Qlik tools and be able to take your data analytics journey to new heights.
Table of Contents (17 chapters)
Part 1:Concepts of Machine Learning
Part 2: Machine learning algorithms and models with Qlik
Part 3: Case studies and best practices


In this chapter, we first learned what data literacy means as a concept. We investigated the methods of being data literate and discussed how to apply these methods to our work. Being able to read and utilize data is an important skill in the modern world, since there is an increasing amount of data around us all the time.

We discovered what informed decision-making is and went through the process of making informed decisions with data, analytics, and machine learning. This process will be our guiding light in the next chapter when we are starting to lean towards the practice. It will give us guidelines that we will use to form our machine-learning question and when we are defining the solution.

At the end of this chapter, we briefly discussed data strategy and maturity. Data strategy is an important aspect of every modern organization but is also a wide topic. We scratched the surface of how to define the maturity of an organization from a data point of view and what...