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)
10
And now?
12
Other Books You May Enjoy
13
Index

Who this book is for

The learning path offered by this book has been designed with three types of readers in mind:

  1. Knowledge workers of any background, level, and functional expertise who use data to facilitate data-based decisions or inform others about the state of the business with reports, visuals, and ad-hoc analyses. They want to modernize and expand their data fluency to both simplify their regular data-related chores and augment their business impact. Today, they mainly use Excel to manage data and reports: they understand the need to upgrade to more powerful tools but do not know where to start and have zero programming experience. Even if proficient with Excel, they feel the need to automate their workflows to gain personal productivity. They would also like to build professional-looking, self-serve dashboards and automate as much as possible the process for updating them, so they can focus on interpreting the data and go beyond the plain figures. This book will give them the tools and techniques for reaching these objectives.
  2. Business managers of any functional background—including marketing, sales, finance, IT, and HR—who want to gain first-hand experience in data analytics to understand and unlock the true potential of data in their area of responsibility. They don't have the technical expertise and do not plan to become specialists but would like to understand what's possible and guide their teams through the required transformation. They want to be a source of help instead of a burden and are ready to roll up their sleeves and study. Today, many senior leaders appreciate the potential value of analytics but don't know how to make it happen in their organizations. This book will help them touch with their own hands the value creation opportunities and finetune their expectations with their teams appropriately. How many of us dream of having bosses who know what they are asking for? This book makes managers aware, reasonable, and confident when setting expectations on business data analytics.
  3. Business and data science students and junior professionals who already have theoretical and academic knowledge but have little to zero business experience. They would like to see how their knowledge is used in companies in practice to have a vertical start-up in their first jobs. After so much theory, compartmentalized across different disciplines (computer science, data science, statistics, and business), they crave experiencing the end-to-end process which leads from raw data to actionable business decisions. They are looking for a book full of real-world examples: this is exactly what they are going to get here.

No prior knowledge is required for any of these types of readers. The little math you will find around the chapters is always introduced very gently and stays to the level needed to put analytics "at work," leaving it to the readers to dive deeper as they please. I wrote this book to make data analytics accessible to everyone who wants to invest some time to self-develop. I am thrilled that you are one of them.