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Data Analytics Made Easy

Data Analytics Made Easy

By : De Mauro
4.7 (12)
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Data Analytics Made Easy

Data Analytics Made Easy

4.7 (12)
By: 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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10
And now?
12
Other Books You May Enjoy
13
Index

Finalizing your visual

On top of the specific guidelines to follow for each type of chart, which we have encountered in the previous pages, there are some general quality design rules that apply every time. The common denominator of such rules brings us back to where we started at the beginning of the chapter: minimalism is the ultimate key to effective data visualization.

Yale University professor Edward Tufte has been a pioneer in modern data visualization. One of the key concepts he introduced is the data-ink ratio, which describes the prevalence of data-driven visual elements in a chart. Consider all the "ink" you use in a chart to draw the essential, non-redundant display of data information: if we erased these chart elements, we would also remove the underlying business message we wanted to convey. Now think about the total ink you would need to print the chart, which includes non-required legends, background pictures, unneeded text, and so on. Tufte found out that...

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Data Analytics Made Easy
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