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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

Chapter 1

For a comprehensive review of data analytics job families and related skills, you can check out some of my research papers on the topic, in particular: De Mauro, A., Greco, M., Grimaldi, M., Ritala, P. "Human resources for Big Data professions: A systematic classification of job roles and required skill sets." Information Processing & Management 54.5 (2018): 807-817, https://doi.org/10.1016/j.ipm.2017.05.004.
To get a visual summary of the plethora of tools available in the broader area of data analytics, you can review the Data & AI Data Landscape, which is updated every year, by Matt Turck: http://tiny.cc/datalandscape.
To learn more about the ongoing convergence of operational research and machine learning into prescriptive analytics, you can read Lepenioti, K., Bousdekis, A., Apostolou, D., & Mentzas, G. "Prescriptive analytics: Literature review and research challenges." International Journal of Information Management 50 ...

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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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