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

Modeling your data

Data tables are hardly useful when they lie apart. In fact, by organizing them together in a database, we amplify their overall value as we unveil patterns and connections across data points. That is why data is typically stored in an ensemble of different tables connected with each other to virtually form a single body called a Data Model. When you work with multiple tables, it is beneficial to "visualize" what the underlying data model looks like: this gives you the ability to anticipate ways to leverage the data and interpret it correctly.

We shall bring the concept of a data model to life by going through a business example. Let's imagine that we own a small store selling musical instruments. Our business model is pretty simple: we order instruments from manufacturers and store them in a warehouse. Customers call at our shop and get the chance to try a few instruments before deciding whether to purchase or not. Our most loyal customers sign...