The amount of data that gets generated on a daily basis is increasing each passing day. That is why companies across the globe are hiring data scientists to turn data into insightful and actionable information.\r\n\r\nNow that everyone knows that the data scientists role is the sexiest job of the 21st century, numerous young professionals are applying for these jobs. But what should a young professional do to make sure that he\/she stands out from the crowd? Apart from a sparkling resume and tailor-made skill-set, is there anything else that a data scientist should inculcate in his\/her personality\r\n\r\nIn this article, Analytics India Magazine lists down top 11 non-technical books that every single data scientists should inculcate and internalise to stand out from the crowd. There are no cash awards, certificates or LinkedIn recommendations for reading these books \u2014 but the life lessons and work ethics that the reader garners from them are priceless.\r\n1. Thinking, Fast And Slow by Daniel Kahneman (Penguin, 2012 | \u20b9276)\r\nThis international bestseller authored by noted economist and psychologist Daniel Kahneman takes the readers on a fascinating journey by dissecting the mind and goes onto explain two distinct systems that affect our way of thinking and making choices. Of these two systems, one is intuitive, emotional yet fast while the other one is more logical and deliberative. As every data scientist has to have the qualities of a storyteller as well as a decision-maker, this book is a perfect read for him\/her.\r\n2. How Not to be Wrong by Jordan Ellenberg (Penguin, 2014 | \u20b9399)\r\nHow Not to Be Wrong: The Power of Mathematical Thinking showcases the surprising revelations behind questions like, \u201cWhat does public opinion really represent,\u201d or \u201cHow likely are you, really, to develop cancer?\u201d The book tries to answer such questions using the mathematician\u2019s method of analysing life and exposing the hard-won insights of the academic community to the layman \u2014 minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia\u2019s views on crime and punishment, the psychology of slime molds, what Facebook can and can\u2019t figure out about you, and the existence of God.\r\n3. Understanding Comics by Scott McCloud (William Morrow, 1994 | \u20b91,358)\r\nMichael Hochster, the director of Data Science at Stitch Fix, says, \u201cI recommend this book because a lot of what data scientists do is to communicate using a combination of images and words, just like in comics. The author is both a skilled craftsman and an excellent explainer. The book is full of thoughtful discussion and examples. I found it far more useful and stimulating than most of the standard literature on data visualisation.\u201d\r\n4. Creativity Inc by Ed Catmull (Bantam Press, 2014 | \u20b9396)\r\nThis book is a great read for managers who want to lead their employees to new creative heights. It is termed as a manual for anyone who strives for originality, and the first-ever, all-access trip into the nerve centre of Pixar Animation Studios \u2015 into the story meetings, the postmortems, and the \u2018Braintrust\u2019 sessions where art is born. It is, at heart, a book about how to build and sustain a creative culture\u2015but it is also, as Pixar co-founder and president Ed Catmull writes, \u2018an expression of the ideas that I believe make the best in us possible.\u2019\r\n5. The Black Swan: The Impact of the Highly Improbable by Nassim Nicholas Taleb (Penguin, 2008 | \u20b9381)\r\nThis book focuses on Taleb\u2019s Black Swan Theory. Through a number of examples, the author aims to show his readers how rare and unpredictable events have a deep and lasting impact on a person's life. Human beings tend to try and rationalise such happenings almost immediately after they happen. This is an almost impossible task since such events are based on chance. A number of other topics, which relate to aesthetics, ways of life, knowledge and much more, have been discussed in this book.\r\n6. Stress-Proof by Mithu Storoni (Penguin, 2017 | \u20b9419)\r\nTranslating complex scientific findings into straightforward and actionable advice, this book moves forward a working professional\u2019s understanding and wellness in a meaningful way. Living the hectic lives the data scientists live, this book, where each chapter examines a stress agent we all face -- including sugar, inflammation, an out-of-sync body clock, cortisol and emotional triggers -- presents simple ways to block it. It gives solutions in the form of everyday changes in diet, lifestyle, behaviour and exercise. It also includes advice and surprising strategies using music, eye movements, body temperature and more.\r\n7. The Emperor's New Mind by Roger Penrose (Oxford University Press, 2016 | \u20b9580)\r\nCan a computer eventually do everything a human mind can do? Wolf Prize-winning physicist Roger Penrose talks about his view that there are some facets of human thinking that can never be emulated by a machine. In this book, Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness.\r\n8. The Life-Changing Magic of Tidying Up by Marie Kondo (Ten Speed Press, 2014 | \u20b9963)\r\nData scientists can sometimes be so overwhelmed by their work pressures that it may sometimes become difficult to prioritise. In this not-so-directly-related book, data scientists can find solace in simple, easy-to-adopt methods of organisations and decluttering. Because it is a truth universally acknowledged that a clean, tidy workplace and home are the perfect breeding ground for concentration and creativity.\u00a0\r\n\r\nIn this best-seller, Japanese cleaning consultant Marie Kondo takes tidying to a whole new level, promising that if you properly simplify and organise your home once, you\u2019ll never have to do it again. Most methods advocate a room-by-room or little-by-little approach, which doom you to pick away at your piles of stuff forever. The KonMari Method, with its revolutionary category-by-category system, leads to lasting results.\r\n9. Deep Work: Rules for Focused Success in a Distracted World by Cal Newport (Little Brown Book Group, 2016 | \u20b9278)\r\nIn his new book, Cal Newport talks about how professionals of today have started valuing quantity over quality; and how this has turned young professionals of today into puppets who try to indulge in extensive multitasking, dealing with multiple emails and projects. This prevents them from doing 'deep work'; which is focused work free from all other distractions. This also means that the professionals of today should sort out their priorities.\r\n10. Tools of Titans: The Tactics, Routines and Habits of Billionaires, Icons and World-Class Performers by Timothy Ferriss (Random House, 2016 | \u20b9487)\r\nDuring his podcast The Tim Ferriss Show, Ferriss got to interview a slew of celebrities and successful personalities. He says that this book contains the distilled tools, tactics, and \u2018inside baseball\u2019 you won\u2019t find anywhere else. The book contains answers to questions like, \u201cWhat do these people do in the first sixty minutes of each morning? What do their workout routines look like, and why? What books have they gifted most to other people? What are the biggest wastes of time for novices in their field? What supplements do they take on a daily basis?\u201d Data scientists as a creative breed can learn much from these successful people and apply the knowledge in their daily lives.\r\n11. Adventures of Sherlock Holmes by Sir Arthur Conan Doyle (Penguin | \u20b9230)\r\nA classic fiction tome might seem like an unlikely fit in this list, but let us not forget that it was this legendary character who most showed trust in the power of data. The Baker Street detective was most loved for his deductive powers, but when he explained the process behind his conclusions, it was very clear that he relied on information, observation and data.