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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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,
  • 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:
  • 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 ...