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

Segmenting consumers with clustering

In this tutorial, you will re-enter the shoes of the business analyst working for the online retailer we encountered in Chapter 3, Transforming Data. This time, instead of automating the creation of a set of financial reports, you are after a seemingly sexier objective. The Customer Relationship Management (CRM) team is looking for a smarter way to communicate with those customers who opted-in to receive regular newsletters. Instead of sending a weekly email equal for all, the CRM manager asked you to find a data-based approach for creating a few meaningful consumer segments. Once segments are defined, the CRM team can build multiple messages, one for each segment. By doing so, they will offer a more personalized (and engaging) experience for the entire customer base, which will ultimately affect customer loyalty and drive sustainable revenue growth.

Unsupervised learning offers a proven methodology that can meet this business need: by using...