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Principles of Strategic Data Science - Creating value from data, big and small (Paperback)
Loot Price: R666
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Principles of Strategic Data Science - Creating value from data, big and small (Paperback)
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Take the strategic and systematic approach to analyze data to solve
business problems Key Features 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 Book
DescriptionPrinciples of Strategic Data Science is created to help
you join the dots between mathematics, programming, and business
analysis. With a unique approach that bridges the gap between
mathematics and computer science, this book takes you through the
entire data science pipeline. The book begins by explaining what
data science is and how organizations can use it to revolutionize
the way they use their data. It then discusses the criteria for the
soundness of data products and how to best visualize information.
As you progress, you'll discover the strategic aspects of data
science by learning the five-phase framework that enables you to
enhance the value you extract from data. The final chapter of the
book discusses 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. What you will learn
Get familiar with the five most important steps of data science Use
the Conway diagram to visualize the technical skills of the data
science team Understand the limitations of data science from a
mathematical and ethical perspective Get a quick overview of
machine learning Gain insight into the purpose of using data
science in your work Understand the role of data science managers
and their expectations Who this book is forThis book is ideal for
data scientists and data analysts who are looking for a practical
guide to strategically and systematically use data. This book is
also useful for those who want to understand in detail what is data
science and how can an organization take the data-driven approach.
Prior programming knowledge of Python and R is assumed.
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