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)
10
And now?
12
Other Books You May Enjoy
13
Index

Chapter 7

  • On the superiority of vision on the other senses or, like John Medina puts it, on the fact that "vision trumps all other senses", see: Medina, J. J., 12 Principles for Surviving and Thriving at Work, Home and School. Pear Press, 2009.
  • On the importance of vision in human cognition, which includes Prof. David William's claim on the portion of cortex dedicated to vision, visit https://www.rochester.edu/pr/Review/V74N4/0402_brainscience.html.
  • To learn more about preattentive attributes, you can read the book Few, S. "Show me the numbers." Analytics Pres (2004) or read Few's article, "The visual perception of variation", at https://www.perceptualedge.com/articles/visual_business_intelligence/the_visual_perception_of_variation.pdf.
  • An earlier version of preattentive attributes was published in 1984 by Cleveland and McGill from Bell Labs. The paper exhibits a number of vintage charts from the 80s, and it is worth a read:...