Book Image

Data Analytics Made Easy

By : Andrea De Mauro
4 (1)
Book Image

Data Analytics Made Easy

4 (1)
By: Andrea De Mauro

Overview of this book

Data Analytics Made Easy is an accessible beginner’s guide for anyone working with data. The book interweaves four key elements: Data visualizations and storytelling – Tired of people not listening to you and ignoring your results? Don’t worry; chapters 7 and 8 show you how to enhance your presentations and engage with your managers and co-workers. Learn to create focused content with a well-structured story behind it to captivate your audience. Automating your data workflows – Improve your productivity by automating your data analysis. This book introduces you to the open-source platform, KNIME Analytics Platform. You’ll see how to use this no-code and free-to-use software to create a KNIME workflow of your data processes just by clicking and dragging components. Machine learning – Data Analytics Made Easy describes popular machine learning approaches in a simplified and visual way before implementing these machine learning models using KNIME. You’ll not only be able to understand data scientists’ machine learning models; you’ll be able to challenge them and build your own. Creating interactive dashboards – Follow the book’s simple methodology to create professional-looking dashboards using Microsoft Power BI, giving users the capability to slice and dice data and drill down into the results.
Table of Contents (14 chapters)
And now?
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Transforming Data

Now that we have the basics of KNIME at hand, we can move to the next level. In this chapter, we will learn how to transform data to make the best out of it systematically. The following pages will show how to work with multiple tables, aggregate data points, apply expressions, and iterate through your workflows to automating their execution. All these new skills will make you an autonomous user of KNIME when manipulating real-world data.

This chapter will answer the following questions:

  • What is a data model, and how can I visualize it?
  • How can I combine several data tables?
  • How can I aggregate data points and calculate formulas?
  • How can KNIME automate the creation of summary reports?
  • What do variables and loops look like in KNIME?

This chapter will end with a full tutorial based on real data and a very realistic business case: it will be an opportunity to put into practice all you've learned so far about KNIME while confronting...