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 of
The 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 scientists Data 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 Learn Understand 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 For Startup 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.
