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Principles of Strategic Data Science
Principles of Strategic Data Science

Principles of Strategic Data Science: Creating value from data, big and small

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Key benefits

  • Gain detailed information about the theory of data science
  • Augment your coding knowledge with practical data science techniques for efficient data analysis
  • Learn practical ways to strategically and systematically use data

Description

Mathematics and computer science form an integral part of data science, and understanding them is crucial for efficiently managing data. This book is designed to take you through the entire data science pipeline and help you join the dots between mathematics, programming, and business analysis. You’ll start by learning what data science is and how organizations can use it to revolutionize the way they use their data. The book then covers the criteria for the soundness of data products and demonstrates how to effectively visualize information. As you progress, you’ll discover the strategic aspects of data science by exploring the five-phase framework that enables you to enhance the value you extract from data. Toward the concluding chapters, you’ll understand the role of a data science manager in helping an organization take the data-driven approach. By the end of this book, you’ll have a good understanding of data science and how it can enable you to extract value from your data.

Who is this book for?

This book is for data scientists and data analysts who are looking for a practical guide to help them strategically and systematically use data. You’ll also find this book useful if you simply want to understand what data science is and how an organization can adopt a data-driven approach. Prior knowledge of Python and R programming is assumed.

What you will learn

  • Discover the five most important steps of data science
  • Use the Conway diagram to visualize a data science team's technical skills
  • Understand the limitations of data science from a mathematical and ethical perspective
  • Get a quick overview of machine learning
  • Understand the purpose of using data science in your work
  • Explore the role of data science managers
  • Gain insight into the purpose of using data science in your work
  • Understand the role of data science managers and their expectations

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 03, 2019
Length: 104 pages
Edition : 1st
Language : English
ISBN-13 : 9781838985509
Category :
Languages :
Concepts :

What do you get with eBook?

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Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning

Product Details

Publication date : Jun 03, 2019
Length: 104 pages
Edition : 1st
Language : English
ISBN-13 : 9781838985509
Category :
Languages :
Concepts :

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Table of Contents

5 Chapters
Chapter 1: What is Data Science? Chevron down icon Chevron up icon
Chapter 2: Good Data Science Chevron down icon Chevron up icon
Chapter 3: Strategic Data Science Chevron down icon Chevron up icon
Chapter 4: The Data-Driven Organization Chevron down icon Chevron up icon
References Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(1 Ratings)
5 star 100%
4 star 0%
3 star 0%
2 star 0%
1 star 0%
Amazon Customer Jan 04, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent pithy analysis, with detailed explanations and examples of data science. I am not interested in the history of data science covered in this book. HOWEVER, I am very glad that I kept reading because Dr Prevos is able to say in a paragraph what many other books do not achieve in two pages (this is the fifth data science book that I have read this week). I thoroughly recommend this book, an excellent combination of technical terms and processes, explained in language accessible to everyone, even with little or no prior knowledge of data science.
Amazon Verified review Amazon
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