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)
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Extending Your Toolbox

Getting up to speed with the latest tools and novel techniques in data analytics is surely a never-ending process. In this field, you need to be ready to update and expand your knowledge continuously. So far in this book, we have acquired a number of vital, application-agnostic data techniques such as data cleaning and modeling, machine learning, data visualization, and storytelling. We have also learned how to apply them through a solid application toolbox made of KNIME and Power BI. As we approach the end of our journey, we should see what else is available and how to integrate all the applications together to make the best out of all of them.

In particular, we will cover the following questions:

  • What is Tableau, and how can I use it for visualization and storytelling?
  • What is Python, and how do I get started with it?
  • How can I boost my workflows by integrating Python or any other code?
  • How can I use KNIME extension packages to add functionalities...