What Is Data Science?

by Mike Loukides

We've all heard it: according to Hal Varian, statistics is the next sexy job. Five years ago, in What is Web 2.0, Tim O'Reilly said that "data is the next Intel Inside." But what does that statement mean? Why do we suddenly care about statistics and about data? This report examines the many sides of data science -- the technologies, the companies and the unique skill sets.The web is full of "data-driven apps." Almost any e-commerce application is a data-driven application. There's a database behind a web front end, and middleware that talks to a number of other databases and data services (credit card processing companies, banks, and so on). But merely using data isn't really what we mean by "data science." A data application acquires its value from the data itself, and creates more data as a result. It's not just an application with data; it's a data product. Data science enables the creation of data products.

Genres: Technology, Science, Nonfiction, Computer Science, Programming, Business, Professional Development

23 pages, Kindle Edition

First published April 1, 2011

Reviews

[RM(Alwaysdaddygirl)]

Good!

Some reasons for 4 stars:
-Interesting
-I did not check all the references. There is a plethora of references.

🇺🇸

[Gourav Kumar]

Precise and understandable

4 out 5 because it tells you what is data science and not how to be a data scientist.
Great with explanations it covers all the aspects of data science

[Santiago Ortiz]

This book is not about data science but about tools, it certainly doesn't answer title's question.

[Ankur Pandey]

Quite informational but deviates from topic. Instead of data science it begins to discuss tools.

[Gaurav Seth]

Basic

Very basic. Doesn't go in deep. Fine for starters. Some examples are good but does not take a deep dip in data

[Amyth Banerjee]

One of the most simple and comprehensive introduction to the world of Data science. A subject which otherwise maybe super technical and filled with lots of statistics and programming, this book focuses on the bigger picture and gives sufficient examples to understand the context. For those intending to get inducted into this field, it can't get better than this.

[Ed Barton]

Good Intro

The question that comprises the title is far bigger than can be covered in this short read. However, the book gives you the first overviews of data science, data science tools, and the challenges faced by data scientists. If you’re getting into the field, this is a good spot to start your research.

[Anne]

Just a lot of name-dropping, and a lot less explaining. Although I got a picture of what data science is more or less, I think it could have been said in 2 pages, and could have done with a other 20 pages going in-depth on the processes, instead of the name-dropping.

[Antariksa]

Very brief introduction to what data science is, how does one work with it, and why people make such a big deal out of it. Although this book won't teach you how to be a data scientist, I think this is a decent point of departure for anyone wishing to learn to analyze data.

[meesh]

Useful, short overview of what data science is/used for. I found some of the language quoted from Patil around hard scientists v software developers unnecessarily derogatory and self aggrandizing, though not entirely without basis in reality.

[Anu Chacko]

Simple language introduction overview on data science. Finished reading in 30 minutes.

Not much technical but only overview with good references for further explorations. Ideal book for someone with basic idea and want to know scope of subject

[Snehashis Majumdar]

Good

The book provides a brief and educational overview of data science and how it can be useful and who should understand the topic.

[Arun Rajan]

Beginners guide for DS

Introduction to data science explained (briefly). Limited explanation but worth a read. Could have improved the content with a bit more intense content.

[Bill]

Free for Kindle.

[Shilpam]

Okay quick read

Gives you a basic understanding of data science with all relevant needed hyperlinks. There could have been more details added to the content list.

[Ashwini]

Start here if you want to understand the beautiful and intriguing world of Data Science.

[Ashish Om Gourav]

A precursory glance into the world of Data Science. It sheds some light on how Data Science is practised and how munging the data is a key part of the industry.

[Eren Avsarogullari]

A high level summary on the evolution of data, which emphasizing its generation, storage, processing and extracting the value.

[Camila]

It was a good introduction to the topic

[Eelco den Heijer]

Only 22 pages? It's not really a book, more like a chapter 1 of an Introductory book.

Not really recommended.

[Lokesh Joshi]

Very very intro level

It’s a very intro level and somewhat repetitive, seems to be created from a blog author wrote. Good read for someone who is very new to the field.

[Henrique Donati]

Good source of resources to learn

The book doesn't have all the answers itself, but instead, it contains a huge collection of resources that are hyperlinked, such as videos, articles, examples, that will lead you to the answers you are looking for!

Great overview and great resources.

[Maciej Janiec]

Maybe the edition I got from Amazon wasn't complete.

There was a note at the end of the "book" about the possibility of "upgrading" it, but no details why I should do it were presented.

Still the book or rather a booklet was quite general, containing just a couple of potentially interesting things - mainly links to some web pages, references to other book and online courses.

What I had looked like a rather lengthy advertisement for other O'Reilly publications...

[Brian Darrow]

Exactly what the title says

This book won't make you a data scientist, but in about 30 minutes of reading, it will allow you to speak intelligently about the subject at a cocktail party. More importantly, it's a fantastic overview of data science and it provides copious links and references to more in depth information. If you are interested in data science but don't have a clue where to start, this book is for you.

[Amirhossein Kalari]

If you're a absolute beginner in overall computer, or programming, or similar, and you want to read this book, you must change your mind because this book is not for you. Also, this book doesn't answer the title, rather it just talks about "data is important" and "there're things can help you through working with data" and just this.

This is hard, sometimes, for people to picture the real importance of Data Science and the magic of using data to extract something valuable.

[Jason]

Good overview.

Good overview.

While short on applicable practices in data interpretation, this book gives a high-level overview of the core concepts. And probably convinced me to go back to school. An easy and worthwhile read.

[Andrew D KIm]

Good enough to understand the general topic

A very general overview with some good references. Slightly dated at this point though. A few in depth examples would have been beneficial. This book is ideAl for someone just looking to understand the broad topic.

[J. Arturo]

Good start, a little confusing in some parts

You can get a good idea of what Data science is, but in some points it's a little confusing . Give it a chance you might find something useful.

[Sreedhar Peddineni]

Broad ranging overview of data science in a short book format - but it is just an overview various facets of Data Science and does not cover any area in depth.

[Jerome Gentolia]

Broad introduction of Data Science. Where is the rest of the book? The upgrade teaser does not really give enough information on whether you are getting more chapters.