As time flies, now big tycoons are more focused on data. That's the reason many of the people building businesses today are putting analytics and data science at the center of their strategy and operations. Following are the books on Data Science that take you in deep with the concepts and develop your skills:
The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses: This isn't exactly a data science book, but it contains many insights that could drive your business forward through innovation and technology. Written by Eric Ries, this book reveals some proven strategies for implementing new technology in business situations and maintaining flexibility in the face of technological change.
Lean Analytics: Use Data to Build a Better Startup Faster:Whether you're a startup founder aiming to disrupt an industry or an intrapreneur hoping to bring change from within, this book can help you by teaching the right way to take your business from initial idea to market, through the use of analytics and data.
Big Data at Work: Dispelling the Myths, Uncovering the Opportunities: It could be hard to understand how important big data can be in the workplace but this data science book gives a solid overview of the technology and its implications. It also provides a more business-focused explanation on success factors in implementing big data projects and hiring a good team of data scientists.
Keeping Up with the Quants: Your Guide to Understanding and Using Analytics: No matter your interests or the industry you're working in, the world is full of data. To be a successful manager, it's more important than ever to harness and make sense of this data. This book, inspired in part by the Moneyball story, discusses the quantitative analysis for decision making, and the application of data science in business.
Data Science for the Layman: No Math Added:Everyone has to start somewhere, and this book on data science is perhaps the best way for a layman to get some knowledge of the industry and the science itself. This book promises an absence of math, a gargantuan task in the algorithm-based industry. However, by dedicating each chapter to the works of every important algorithm in data science, it allows for a very practical understanding of the knowledge that will require later on in your journey.
Data Analytics Made Accessible: 2017 Edition: The topic of data science can often be dense, locked behind walls of chunky and unreadable text but not with this data science textbook. Concise and conversational, this is an easy read that is still filled to the brim with important knowledge, notably the concrete real-life case studies displaying how the science can be applied in business situations. It even includes a short R tutorial. This particular edition also gives some valuable insights and suggestions based on the response of reviewers of previous editions, making for an updated and modern view of the advancements in data science.
The Art of Data Science: It can be tough for some to view data analytics as anything other than a rigid and difficult-to-acquire skill, given its focus on fundamental knowledge of mathematics and statistics. However, in reality, not only can the interpretation of data produce a wide range of useful business insights, but the very analysis of data is much more commonsensical than you might expect.
Data Science for Dummies: Not surprisingly, this book is a fantastic starting point for anyone seeking to pick up this skill. It gives a quick overview of all things data science, with a broad focus on a variety of business cases, giving you a good idea of what to expect when making use of your budding company's databases. This textbook-like resource will help you decide whether your startup could benefit from further exploration of data, even going down into the details of which type of analysis can be applied to certain business cases.
The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists: Now that you have a good idea of what to expect from the science and backend aspects of data science, it's also important to have a grasp on the more human aspect of the job. This book takes a different approach from most others, interviewing veterans of the industry, like Uber's former data science chief Kevin Novak, and getting their input on how data analytics relates to business and society at large. This book won't just equip you with the rough technical know-how, but will also give you industry tips and tricks to launch your learning journey.
Data Science for Business: Written with the everyday businessman in mind, this data science book is a great way to dive into big data analytics as it relates to your business needs, introducing useful data analysis principles. Through this book, the authors aim to provide enough knowledge and instill enough confidence in any business-person, so that they can make the most efficient use of their data scientists and analytics teams.