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Roman's Data Science: How to monetize your data
An introduction to the field of data analysis written in jargon-free language that is not bogged down by programming code and mathematical formulas. It covers the most essential topics in the fields of data science, machine learning and business intelligence that you are likely to come across on a regular basis.
The main goal is to help readers get the most out of their data, make business decisions and create information products - all without paying over the odds.
In a career spanning over 20 years, the author has worked as a junior data analyst, headed up the analytics division of an $10-billion company and co-founded a recommendation systems startup. The text was edited by a professional journalist. It contains QR codes and links with links you can follow if you want a deeper understanding of the topics covered.
This book is intended for readers who want to try their hand at data analysis and develop data-driven services. Here are some facts about it:
- In Russia, the book was sold out in three weeks.
- The book is based on the author's personal experience - it is not a boring textbook!
- It provides a complete Data Science picture without coding and math.
Those who are new to data science will learn exactly what the business needs in this area are, as well as different approaches to data analysis and an effective way to master machine learning.
Startups will learn how to get their data science divisions up and running quickly. They will also be introduced to three approaches to analyzing A/B tests.
Managers will learn about task management, money efficiency and the hypothesis pipeline in data science.
The main goal is to help readers get the most out of their data, make business decisions and create information products - all without paying over the odds.
In a career spanning over 20 years, the author has worked as a junior data analyst, headed up the analytics division of an $10-billion company and co-founded a recommendation systems startup. The text was edited by a professional journalist. It contains QR codes and links with links you can follow if you want a deeper understanding of the topics covered.
This book is intended for readers who want to try their hand at data analysis and develop data-driven services. Here are some facts about it:
- In Russia, the book was sold out in three weeks.
- The book is based on the author's personal experience - it is not a boring textbook!
- It provides a complete Data Science picture without coding and math.
Those who are new to data science will learn exactly what the business needs in this area are, as well as different approaches to data analysis and an effective way to master machine learning.
Startups will learn how to get their data science divisions up and running quickly. They will also be introduced to three approaches to analyzing A/B tests.
Managers will learn about task management, money efficiency and the hypothesis pipeline in data science.
- GenresNonfictionBusiness
245 pages, Kindle Edition
First published August 16, 2021
10 people are currently reading
279 people want to read
About the author
Roman Zykov
2 books2 followers- 20 years of experience in data analysis, holds a master’s degree in applied mathematics and physics.
- Founded Retail Rocket, the leading Russian provider of e-commerce recommendation systems (SaaS) with offices in Europe and South America.
- Created analytics from scratch for the Russian online retailer Ozon.ru (worth $10 billion Nasdaq).
Roman Zykov was born in 1981. After completing his undergraduate studies in 2004, Roman went on to earn a master’s in Applied Physics and Mathematics at the Moscow Institute of Physics and Technology (MIPT).
Roman started his career in data science in 2002 as a technical consultant at StatSoft Russia– the Russian office of the U.S. developer of the STATISTICA statistical data analysis software. In 2004, he was hired as head of the analytical department of the Ozon.ru online store, where he created analytical systems from scratch, including web analytics, database analytics and management reporting, while also contributing to the recommendation system.
In 2009, he advised on a number of projects for Fast Lane Ventures investment fund and the gaming industry.
In 2010, Roman was hired to lead to analytics department of the online retailer Wikimart.ru.
In late 2012, he co-founded RetailRocket.ru, a marketing platform for online stores. The company is currently the undisputed market leader in Russia and successfully operates in Chile, the Netherlands, Spain and several other countries.
Roman ran the blog Analytics in Practice on the now defunct KPIs.ru from 2007 where he evangelized data analysis as it applies to business problems in ecommerce. He has spoken at numerous industry conferences, including the Russian Internet Forum, iMetrics and Gec 2014 (with Arkady Volozh of Yandex), as well as at business conferences in Dublin and London, the U.S. Embassy (American Center in Moscow), and 10 About the Author Sberbank University. He has also published in PwC Technology Forecast, ToWave, Vedomosti and Sekret firmy.
In 2016, Roman has talked about on hypothesis testing at MIT in Boston (ACM RecSys).
In 2020, he was nominated for a CDO Award.
- Founded Retail Rocket, the leading Russian provider of e-commerce recommendation systems (SaaS) with offices in Europe and South America.
- Created analytics from scratch for the Russian online retailer Ozon.ru (worth $10 billion Nasdaq).
Roman Zykov was born in 1981. After completing his undergraduate studies in 2004, Roman went on to earn a master’s in Applied Physics and Mathematics at the Moscow Institute of Physics and Technology (MIPT).
Roman started his career in data science in 2002 as a technical consultant at StatSoft Russia– the Russian office of the U.S. developer of the STATISTICA statistical data analysis software. In 2004, he was hired as head of the analytical department of the Ozon.ru online store, where he created analytical systems from scratch, including web analytics, database analytics and management reporting, while also contributing to the recommendation system.
In 2009, he advised on a number of projects for Fast Lane Ventures investment fund and the gaming industry.
In 2010, Roman was hired to lead to analytics department of the online retailer Wikimart.ru.
In late 2012, he co-founded RetailRocket.ru, a marketing platform for online stores. The company is currently the undisputed market leader in Russia and successfully operates in Chile, the Netherlands, Spain and several other countries.
Roman ran the blog Analytics in Practice on the now defunct KPIs.ru from 2007 where he evangelized data analysis as it applies to business problems in ecommerce. He has spoken at numerous industry conferences, including the Russian Internet Forum, iMetrics and Gec 2014 (with Arkady Volozh of Yandex), as well as at business conferences in Dublin and London, the U.S. Embassy (American Center in Moscow), and 10 About the Author Sberbank University. He has also published in PwC Technology Forecast, ToWave, Vedomosti and Sekret firmy.
In 2016, Roman has talked about on hypothesis testing at MIT in Boston (ACM RecSys).
In 2020, he was nominated for a CDO Award.
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Displaying 1 - 7 of 7 reviews
November 22, 2021
This book is about data analysis. It is meant to be used by those who are considering a career in the field or implementing a data collection process in their business. Although it contains a good deal of jargon, I found it to be a great overview of the field and relatively easy to follow. I was particularly impressed with the recognition of ethical concerns in data science, because it is increasingly being used as a political weapon. We are less likely to be negatively influenced by manipulated data when we understand how it should be collected and used.
November 3, 2021
An excellent source for persons interested in data analysis, machine learning, etc.
September 19, 2021
Because I'm a native Russian speaker, I read this book in Russian. However, it is also available in English.
As a data scientist, this book was valuable and insightful for me. Currently, I am involved in developing two data-driven solutions in my company. Therefore, I was curious about creating a product, which will solve the problems of our customers and bring them value. I am glad that this book could answer some of my questions and helped me to navigate in asking the right questions in the product developing stage. Moreover, the book highlights what is crucial when you work on developing a data-driven product. Apart from that, I have learned some valuable advice on building a career in data science: from negotiating salary to training machine learning models. So I would recommend this book to data scientists at different stages in their careers. I believe everyone can find something valuable and insightful.
As a data scientist, this book was valuable and insightful for me. Currently, I am involved in developing two data-driven solutions in my company. Therefore, I was curious about creating a product, which will solve the problems of our customers and bring them value. I am glad that this book could answer some of my questions and helped me to navigate in asking the right questions in the product developing stage. Moreover, the book highlights what is crucial when you work on developing a data-driven product. Apart from that, I have learned some valuable advice on building a career in data science: from negotiating salary to training machine learning models. So I would recommend this book to data scientists at different stages in their careers. I believe everyone can find something valuable and insightful.
October 30, 2023
Книга хороша, но ее нужно изучать в формате книги. Я слушал в формате аудиобука, и было довольно прикольно слышать фразы а-ля: "...и мы строим график, изображенный на рисунке 10". А что там, собственно, нарисовано, непонятно:) Ну и в целом, были неясные моменты, которые следовало бы перегуглить пару раз, мб несколько раз перечитать. Но не в формате аудиобука...
September 27, 2021
An excellent and very useful book. Primarily for managers who want to create an analytics department in their company, but don't know where to start and what to expect.
I sincerely recommend it to professionals, managers, and startup owners.
I sincerely recommend it to professionals, managers, and startup owners.
January 28, 2024
One of the best books I’ve read recently. It covers, in a very clear way, everything the starting data analyst should take into consideration, including the hiring process and what tools to master.
I had so many insights reading this book, huge respect and thanks to the author!
I had so many insights reading this book, huge respect and thanks to the author!
December 22, 2024
I think this is a good book to junior data analysis, have interesting commentary on system recommend, and several source to junior data analysis have an idea how to grow up his career.
Displaying 1 - 7 of 7 reviews