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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I hope you enjoyed as much as I did the intense journey in the vast and fascinating world of data storytelling that this chapter took us through. We can be great data analysts or respected business domain experts. However, in a business organization, we will often lack the full authority required to make decisions freely and make things happen, even if data certifies the validity of our points. Storytelling extends the potential of data analytics as it lets us transform data into value-creating actions.

We started by applying the ageless enablers of persuasion (being credible, offering logical reasoning, and driving emotional engagement) to business data, and we explored the many reasons stories can make a difference in advocating our data-based recommendations. Then, we went through a systematic process for building data stories that stick, leveraging the (simple but effective) 3-act story structure and the five archetypal data scene types. Afterward, we acquired a set...