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)
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Aggregating values

The information contained in a raw data table lies dispersed across all its rows. Often, we need to condense a large table into a smaller and more readable one where its values get aggregated or summarized following a given logic. For instance, if we have a table including all orders received in the last year and want to make sense of our sales' evolution over time, we might prefer to calculate a simpler table that shows the total number of orders generated every month. Instead of having a long table with as many rows as orders, we prefer scanning through its aggregation showing only twelve rows, one for each month.

The simpler way of aggregating data is by using a rather popular database operation called Group By: it combines rows in various groups and aggregates their values within each group. To perform a Group By, you will need to decide two things:

  • First, you must declare which columns define a group. All the rows showing the same values in the...