Capitalizing Data Science?

Description

Can you foresee how your company and its products will benefit from data science? How can the results of using AI and ML in business be tracked and questioned? Do questions like ‘how do you build a data science team?’ keep popping into your head?

All these strategic concerns and challenges are addressed in this book.

Firstly, the book explores the evolution of decision-making based on empirical evidence. The book then helps compare the data-supported era with the current data-led era. It also discusses how to successfully run a data science project, the lifecycle of a data science project, and what it looks like. The book dives fairly in-depth into various today’s data-led applications, highlights example datasets, discusses obstacles, and explains machine learning models and algorithms intuitively.

This book covers structural and organizational considerations for making a data science team.  The book helps recommend the use of optimal data science organization structure based on the company’s level of development. Finally, the book explains data science’s effects on businesses by assisting technological leaders.