Data Science for Business
What You Need to Know about Data Mining and Data-Analytic Thinking
-
-
3.5 • 4 Ratings
-
-
- £26.99
Publisher Description
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.
Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates
Customer Reviews
A perfect journey to the world of Data Science !
In a short summary, I am so glad I came across this book! It’s not only a great introduction to the complex world of data science, it has sparked a real interest in me to dig deeper into this subject.
The book will prove valuable both to readers with business or technical backgrounds, esp. if you want to understand how to harness data to add value to business problems, or how to engage with colleagues working on data mining, analytical models etc.
There are a few mathematical bits to the book – however I would recommend not to be deterred, and take time to wrap your head around those concepts as they would go a long way to add value to your understanding.
Extended review:
I am a business analyst by profession, so I deal with business processes, identifying business needs, and engaging with colleagues from various technical and non-technical backgrounds. Data Science underlies much of the emerging business practices for data driven decision making.
When I picked up this book I had no prior knowledge of this field, but I was looking to develop conceptual understanding and a real world perspective to the field of data science. This book delivers on both those aspects.
I had initially started off with some online courses, but the interest quickly faded off as the concepts discussed were either too detailed or were too generic in introduction. However the simple narration style of the book, and good business application based case development examples made sure that I do not put down this book till I reach the last page.
Now to add a pinch of salt :
Even though content is outstanding, my only critique would be that the book references links and papers which are of much higher difficulty than concepts presented in the book. In case you want to read more into certain topics you might find that there is a longer bridge that still needs crossing.