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 9

  • To learn more about Tableau, I recommend Meier, M., Baldwin, D. Mastering Tableau 2021: Implement advanced business intelligence techniques and analytics with Tableau. Packt Publishing Ltd, 2021 and Loth, A. Visual Analytics with Tableau. John Wiley & Sons, 2019.
  • To begin your first steps in Python, check out: Matthes, E. Python crash course: A hands-on, project-based introduction to programming, No Starch Press, 2019, and then to deep dive on machine learning applications: Raschka, S., Mirjalili, V. Python machine learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2. Packt Publishing Ltd, 2019.
  • A good example of integrating KNIME, Python, and Tableau is Ganzaroli, D., "Data Science With KNIME, Jupyter, and Tableau Using COVID-19 Projections as an Example", Low Code for Advanced Data Science (2021),
  • To learn more about integrating H2O Driverless AI with KNIME, you can refer to this...