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)
1
Part 1:Concepts of Machine Learning
6
Part 2: Machine learning algorithms and models with Qlik
12
Part 3: Case studies and best practices

Data strategy

Data strategy is a crucial element of any organization’s overall strategy, as it enables organizations to leverage data to achieve their objectives. A well-designed data strategy considers the organization’s goals, challenges, and available resources and outlines the steps needed to collect, manage, analyze, and use data effectively.

One of the key components of a data strategy is data governance, which establishes policies and procedures for data management and usage across the organization. Data governance includes defining data ownership, establishing data standards, and ensuring compliance with data regulations. By having a clear understanding of data governance, organizations can ensure that data is being used ethically and securely, which builds trust with stakeholders.

Well-defined data architecture is another cornerstone of a working data strategy. Data architecture involves designing the structure and systems for managing and storing data...