30-Second Data Science: The 50 Key Principles and Innovations in the Field of Data-Gathering, Each Explained in Half a Minute

by Liberty Vittert

30-Second Data Science is the quickest way to discover how data is a driving force not just in the big issues, such as climate change and healthcare, but in our daily lives. 
 
Data science is an entirely new discipline that encompasses a new era of information , from finding criminals to predicting epidemics. But there’s more to it than the vast quantities of information gathered by our computers, smartphones, and credit cards. 
 
Carefully compiled by experts in the field, 30-Second Data Science covers the basic statistical principles that drive the algorithms, how data affects us in every way—science, society, business, pleasure—along with the ethical quandaries and its future promise of a better world.

Each 30-Second entry details a different facet of data science in just 300 words and one picture , showing how the concept of bringing together different types of data, and using powerful computer programs to find patterns no human eye could spot, is already transforming our world.
 
Exploring key ideas and featuring biographies of the people behind them , 30-Second Data Science explains clearly and concisely all you need to know about data science, from basics to ethics.

The 30 Second series presents concise, informative guides to the most important topics which shape the world around us, presenting terms which are key to understanding the subject in  30 seconds, 300 words, and one image.

Genres: Technology, Nonfiction, Computers

160 pages, Hardcover

Published September 29, 2020

Reviews

[Geoff · Rating 4 out of 5]

Gorgeously illustrated, this slim volume is a nice primer for those with little to no exposure to data science. It covers some major basic concepts in a readable way as well as modern and bleeding edge applications of data science. I also liked how it situated data science firmly in the statistical tradition and gave some good introductions to some major historical figures. On the whole, while I didn't learn a lot, I love the art and would recommend this to anyone who wants a quick overview. And I absolutely would love to frame some of the illustrations on my office wall!

**thanks to the editor, publisher, and NetGalley for a free copy in exchange for an honest review.

[Arevik Heboyan · Rating 5 out of 5]

Thanks to NetGalley, authors, and publishers, for the opportunity to read an advanced copy of "30-Second Data Science".
This book is an excellent introduction to the subject of data and data science, with mesmerizing visual material, related facts to each topic, related brief biographies, highlighted main ideas, and very accessible explanations of topics. Do not expect deep dive into topics, this book does what it says: within a couple of minutes and a couple of pages we get an idea of certain use of data and its characteristics.
This is a great tool for students interested in AI, data science, statistics, just to understand what are the uses and main research fields of data usage. It is perfectly visualized and great learning material and introductory tool.

The book touches and elaborates the main uses of data and characteristics of uses in each of the below fields:
-daily use of data
-business use of data
-social/ethical use of data
-medical data & biostatistics
-predictive analytics
-decision making in uncertainty ( my personal favorite and research topic)
-logistics and business process optimization
-shopping, surveillance, and other uses.

Needless to say, this is a definitely 5-star read for me. The amount of research and accessibility for the researches in all academical fields, language, and logical reasoning and transitions, made this book an exceptional material for both students.
I am going to use this in my classes of the theory of psychological research as a mandatory, introductory read, as well as my small research group.

If possible, please share a copy of this book upon printing, I'd definitely treasure it in my library.

[AcademicEditor · Rating 4 out of 5]

This is a good summary book of the main principles and figures in data science. If you have no previous knowledge of the subject, I don't think this is the right guide to learn. But as a review/reference, it would be handy for a classroom. The book design is very nice. I normally don't pay a lot of attention to forewords, but this one was kind of a non-sequitur, and even contained an apparent error in the name of the professor's institution--it's the Faculty of Arts AND Sciences, not OF. Anyway. I also really liked the sidebars of "3-second samples" and "3-second analyses"--they would be great to use with a classroom.

Thank you to the publishers and NetGalley for the opportunity to review a temporary digital ARC in exchange for an unbiased review.

[dani · Rating 3 out of 5]

Found this book in my local library. Data science is one of my many interests so I decided to read this one.

I think that it's a great book for those just getting started with data science. It doesn't have too much information, and even has smaller paragraphs, summing up things.

At the beginning of each section, they had a glossary of key terms, but it would have been better, if it was also included at the bottom of the page that I was reading. For example, I'm reading something that has the term 'causation' in it. I can't remember what it means so I have to go all the way to the beginning of the section.

I also think that the book would have benefited from featuring more diverse data scientists. But it's just a reflection of the kind of people that usually get the attention.

As I mentioned before, it's an okay book for somebody interested in data science. You can explore many different topics, and then look them up in more detail, if anything catches your eye. The book is also very visually appealing, which was another reason why I wanted to take it home with me.

[Ilana · Rating 5 out of 5]

This book is a great read if you are looking to some concise introductions of the principles and main concepts used in the complex field of data science. With data management and evaluation a driving force between a large range of industries and fields - from AI, sports, dating and medicine, to mention only a few - it is important to realize, through simple everyday life examples - what is the relevance of the data models and patterns. In addition, the readers are also introduced to important historical names that pioneered the use of data science.
I was particularly impressed by the graphic part with inspiring illustrations pertinent to the topics explained.
Disclaimer: Book offered by the publisher in exchange for an honest review

[Emma · Rating 5 out of 5]

I have read other books in the 30-second series, so I am familiar with the format. As a novice to the field of data science, this does give a decent overview of theories from a variety of fields such as computing, mathematics, economics and even philosophy. This multi-disciplinary approach is really engaging and you can come away from the book feeling relatively well informed! And you can take it to the bare minimum or go further. If you are in a scientific/mathematical field, or just looking to enhance your knowledge, this is the book for you.

[DaniSanti · Rating 3 out of 5]

Too basic, just some initial concepts about Data Science and then many fields where data science is applied, but no special insights, knowledge; just lot of areas where data science is applied.
I found interesting the short biographies.
Difficult to recommend to someone, maybe if you are very new to data science.

[Khun Min Aung · Rating 3 out of 5]

A quick 2-hour intro to data science covering foundational topics, useful for anybody regardless of background. Data is the new oil and everyone should have a high-level awareness.

[Dee · Rating 5 out of 5]

Quick and easy read! The book does a good job of explaining complex and academic terms related to statistics and data science in lay-man language. The graphics and design of the book suit the topic. The information has been presented in digestible chunks with a focus on real life applications. This approach to explaining topics is effective and consistent throught the book.

I would recommend it as a must-read for anyone interested in the role of data and statistics in our everyday lives. Besides being a good introduction to data science for people from various fields, it could also serve as a source for gathering general knowledge and interesting facts about AI, computer science, big data etc. (such as while preparing for quizzes). The book also prompts the reader to question and reflect on the world they inherit--its systems, flaws, and nuances. Ultimately, it is about so much more than what one may think encompasses “data science”.

Thank you to the publishers and NetGalley for providing me the opportunity to read an advanced copy of 30-Second Data Science".

[Ben · Rating 3 out of 5]

This was a good book, and interesting read.

I really liked the way it was laid out. Very magazine-like graphic design. Impressive.

Would recommend for learning tidbits of data science.

3.7/5

[Sian D · Rating 3 out of 5]

A very simple overview of common data science topics. Would be best for someone who has zero/little knowledge of data science. I liked the three-second and three-minute overviews. Gorgeous illustrations.

[Dr. Tathagat Varma · Rating 1 out of 5]

Not a very useful book at any level, as it neither goes deep into one topic so a learner could deepen their knowledge, nor provides any systematic conceptual ideas that might be useful for a rookie. Not sure what is the purpose of this book or how, whom or where does it help.

[Beth]

I like the layouts of these "30 second" type books - a series of short, digestible sections explaining a complicated concept, using words, quotes, images, numbers and other visuals.

[Rajarajan RJ · Rating 5 out of 5]

Brief introduction to the field of data science!

[Benny · Rating 4 out of 5]

An overview really 30 seconds each article on Data Science from legendary statisticians of the 19th century to data related issues such as ethics being addressed in the 21st century or future.