The Decision Maker's Guide to Data Science for Non-Technical Executives, Managers & Founders | Practical Business Analytics for Strategic Leadership & Data-Driven Decision Making
$23.9
$43.47
Safe 45%
The Decision Maker's Guide to Data Science for Non-Technical Executives, Managers & Founders | Practical Business Analytics for Strategic Leadership & Data-Driven Decision Making
The Decision Maker's Guide to Data Science for Non-Technical Executives, Managers & Founders | Practical Business Analytics for Strategic Leadership & Data-Driven Decision Making
The Decision Maker's Guide to Data Science for Non-Technical Executives, Managers & Founders | Practical Business Analytics for Strategic Leadership & Data-Driven Decision Making
$23.9
$43.47
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Description
Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don't realize is that data science is in fact quite multidisciplinary--useful in the hands of business analysts, communications strategists, designers, and more.With the second edition ofThe Decision Maker's Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientistsData science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker's Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide.What You Will LearnUnderstand how data science can be used within your business.Recognize the differences between AI, machine learning, and statistics.Become skilled at thinking like a data scientist, without being one.Discover how to hire and manage data scientists.Comprehend how to build the right environment in order to make your organization data-driven.Who This Book Is ForStartup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.
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Reviews
*****
Verified Buyer
5
After having read the first edition book and reading “The Data Scientist” newsletter as well as listening to the podcasts and attending the seminars by Dr Stylianos Kampakis on the subject of Data Science, I was eagerly awaiting to read the second edition. Data Science and technology in general are rapidly evolving and it’s important to keep up to date. The first chapter starts with “demystifying” Data Science and clarifying the buzzwords that are used which couldn’t be more apt and useful. There are a lot of misconceptions about Data Science and how statistics are used to produce actionable information and Dr Stylianos Kampakis does an excellent job to present all the aspects of Data Science in a clear and understandable way. And while doing so, keeping the reader interested throughout the book which made it possible for me to read the entire book in one go. It’s one of the best books you can read on the subject of Data Science and is highly recommended.

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