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Principles of Strategic Data Science

Principles of Strategic Data Science

By : Peter Prevos
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Principles of Strategic Data Science

Principles of Strategic Data Science

5 (1)
By: Peter Prevos

Overview of this book

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.
Table of Contents (6 chapters)
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Predicting the Future

Predicting the future has been one of humanity's primary quests for millennia. Forces beyond our direct control influence our lives, and predictions allow us to control the ever-changing world around us to minimize risks to our lives. Before the age of enlightenment, humanity tried to grasp the unpredictability of existence with divination. They studied the movement of stars, animal entrails, tea leaves, and many other things to learn about their fate.

Since the scientific revolution, we no longer look at the stars, study tea leaves, or disembowel animals. Quantitative science is the most successful form of divination ever invented. Many methods are available to predict the future, from a simple linear regression model to more complex random forests and neural networks that are available to connect the past with the future.

Organizations that seek to reap the rewards of data science are often motivated by the capabilities of machine learning and other advanced techniques...

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