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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By completing this chapter, you have made decisive progress in becoming a confident user of data analytics. You have learned how to provide some logic structure to your database by creating a simple entity-relationship model. You have also experienced the essential operations for transforming data assets, such as combining tables and aggregating values as needed. Your analytics toolbox is getting fatter: with fourteen more KNIME nodes at your disposal, you can now build some simple descriptive analytics workflows and automate their executions through loops and variables. The full tutorial has allowed you to gather first-person experience in building a machine that provides systemic answers to recurring needs, starting from a set of business questions and delivering a repeatable process to answer them.

In the next chapter, we will get all of this to the next level by introducing the fundamental concepts of artificial intelligence: we will soon discover how to build machines...