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Data Analytics Made Easy

You're reading from Data Analytics Made Easy Analyze and present data to make informed decisions without writing any code

Product type Paperback

Published in Aug 2021

Publisher Packt

ISBN-13 9781801074155

Length 406 pages

Edition 1st Edition

Concepts

Data Science

Author (1):

Andrea De Mauro

View More author details

Table of Contents (14) Chapters

Preface

1. What is Data Analytics?

2. Getting Started with KNIME FREE CHAPTER

3. Transforming Data

4. What is Machine Learning?

5. Applying Machine Learning at Work

6. Getting Started with Power BI

7. Visualizing Data Effectively

8. Telling Stories with Data

9. Extending Your Toolbox

10. And now?

11. Useful Resources

12. Other Books You May Enjoy

13. Index

What is Data Analytics?

Before we start our journey across the vast and exciting land of data analytics, it is wise to get equipped with an up-to-date map that can show us the way. In this chapter, you will cover all those fundamental concepts you need to visualize, with clarity, the role of data analytics in companies. This will let you spot opportunities for leveraging data and decide how to distill business value out of it. You also want to feel confident about the naming conventions adopted in this domain to avoid any confusion and speak decisively with those around you. Given the hectic development of data analytics these days, it is a wise choice to build a robust foundation of the key concepts before getting our hands dirty with tables and algorithms.

Specifically, within this chapter, you will find answers to the following questions:

What types of analytics can we find in companies?
Who should be designing, maintaining, and using them?
What technology is...

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Authors (1)

De Mauro

De Mauro

Andrea De Mauro has more than 15 years of international experience managing Data Analytics and Data Science organizations. He is currently Head of Business Intelligence at Vodafone Italy. Previously, he served as Director of Business Analytics at Procter & Gamble, looking after the continuous elevation of data analytics in the business and the development of digital fluency across the global organization. He is a professor of Marketing Analytics and Applied Machine Learning at the International University in Geneva, Switzerland, and at the Universities of Bari and Florence, Italy. In his research, he investigates the essential components of Big Data as a phenomenon and the impact of AI and Data Analytics on companies and people. He is the author of popular science books on data analytics and research papers in international journals.

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