Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
| Author | : | |
| Rating | : | 4.15 (711 Votes) |
| Asin | : | B00E6EQ3X4 |
| Format Type | : | |
| Number of Pages | : | 180 Pages |
| Publish Date | : | 2014-05-18 |
| Language | : | English |
DESCRIPTION:
"A must-read resource for anyone who is serious about embracing the opportunity of big data."
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. 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 y
The perfect balance When trying to learn about a new field, one of the most common difficulties is to find books (and other materials) that have the right "depth". All too often one ends up with either a friendly but largely useless book that oversimplifies or a heavy academic tome that, though authoritative and comprehensive, is condemned to sit gathering dust in one's shelves. "Data Science for Business" gets it just right.What I mean might become clearer if I point out what this book is *not*:- It is *not* a computer science textbook with a focus on theoretical derivations and algorithms.- It is *not* a "cookbook" that provi. Let Me Guess At it's core, Data science is the elimination of guess, intuition,hunch and decisions backed by Data .Data Science is ranked the Sexiest Job Of 21st Century by Harvard Business Review. Today there is a tremendous demand for everything "Data Science", Companies need "Data scientists", IT resources are refocusing themselves to be the "Data scientists". Contrary to popular beliefs that Marketing benefits a lot from data science, companies are finding benefits across the spectrum of their operations . Example : A leading Trucking company used Data mining skill to predict which part of the truck is going to break. James Benton Lackey III said Instead it has some businessy sounding bits and the start and end which feel like an afterthought. This isn't really a book about the business applications of data science. Instead it has some businessy sounding bits and the start and end which feel like an afterthought. The middle seems like it was taken from a data mining textbook (or perhaps previously was one). Particularly strangely, it presents some math for machine learning but in a dumbed down way using notation the author invented (the strangest was a replacement for sigma as sum notation).Rather than reading this you're probably better off reading a book about how business might be impacted by machine learning and related things (The Second Mach