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.

    So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems?In this collection of essays and articles, key members of Google's Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You'll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient--lessons directly applicable to your organization.This book is divided into four sections: Introduction--Learn what site reliability engineering is and why it differs from conventional IT industry practicesPrinciples--Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE)Practices--Understand the theory and practice of an SRE's day-to-day work: building and operating large distributed computing systemsManagement--Explore Google's best practices for training, communication, and meetings that your organization can use

    We like to think that we are in control of the future of "artificial" intelligence. The reality, though, is that we -- the everyday people whose data powers AI -- aren't actually in control of anything. When, for example, we speak with Alexa, we contribute that data to a system we can't see and have no input into -- one largely free from regulation or oversight. The big nine corporations -- Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM and Apple--are the new gods of AI and are short-changing our futures to reap immediate financial gain. In this book, Amy Webb reveals the pervasive, invisible ways in which the foundations of AI -- the people working on the system, their motivations, the technology itself -- is broken. Within our lifetimes, AI will, by design, begin to behave unpredictably, thinking and acting in ways which defy human logic. The big nine corporations may be inadvertently building and enabling vast arrays of intelligent systems that don't share our motivations, desires, or hopes for the future of humanity. Much more than a passionate, human-centered call-to-arms, this book delivers a strategy for changing course, and provides a path for liberating us from algorithmic decision-makers and powerful corporations.

    Richard Rumelt shows that there has been a growing and unfortunate tendency to equate Mom-and-apple-pie values, fluffy packages of buzzwords, motivational slogans, and financial goals with “strategy.” He debunks these elements of “bad strategy” and awakens an understanding of the power of a “good strategy.” A good strategy is a specific and coherent response to—and approach for overcoming—the obstacles to progress. A good strategy works by harnessing and applying power where it will have the greatest effect in challenges as varied as putting a man on the moon, fighting a war, launching a new product, responding to changing market dynamics, starting a charter school, or setting up a government program. Rumelt’snine sources of power—ranging from using leverage to effectively focusing on growth—are eye-opening yet pragmatic tools that can be put to work on Monday morning.Surprisingly, a good strategy is often unexpected because most organizations don’t have one. Instead, they have “visions,” mistake financial goals for strategy,and pursue a “dog’s dinner” of conflicting policies and actions.Rumelt argues that the heart of a good strategy is insight—into the true nature of the situation, into the hidden power in a situation, and into an appropriate response. He shows you how insight can be cultivated with a wide variety of tools for guiding yourown thinking.Good Strategy/Bad Strategy uses fascinating examples from business, nonprofit, and military affairs to bring its original and pragmatic ideas to life. The detailed examples range from Apple to General Motors, from the two Iraq wars to Afghanistan, from a small local market to Wal-Mart, from Nvidia to Silicon Graphics, from the Getty Trust to the Los Angeles Unified School District, from Cisco Systems to Paccar, and from Global Crossing to the 2007–08 financial crisis.Reflecting an astonishing grasp and integration of economics, finance, technology, history, and the brilliance and foibles of the human character, Good Strategy/Bad Strategy stems from Rumelt’s decades of digging beyond the superficial to address hard questions with honesty and integrity.From the Hardcover edition.

    Less than 20 years after its founding, it boasts the largest constellation of commercial satellites in orbit, has pioneered reusable rockets, and in 2020 became the first private company to launch human beings into orbit. Half a century after the space race it is private companies, led by SpaceX, standing alongside NASA pushing forward into the cosmos, and laying the foundation for our exploration of other worlds.But before it became one of the most powerful players in the aerospace industry, SpaceX was a fledgling startup, scrambling to develop a single workable rocket before the money ran dry. The engineering challenge was immense; numerous other private companies had failed similar attempts. And even if SpaceX succeeded, they would then have to compete for government contracts with titans such as Lockheed Martin and Boeing, who had tens of thousands of employees and tens of billions of dollars in annual revenue. SpaceX had fewer than 200 employees and the relative pittance of $100 million in the bank.In Liftoff, Eric Berger, senior space editor at Ars Technica, takes readers inside the wild early days that made SpaceX. Focusing on the company’s first four launches of the Falcon 1 rocket, he charts the bumpy journey from scrappy underdog to aerospace pioneer. We travel from company headquarters in El Segundo, to the isolated Texas ranchland where they performed engine tests, to Kwajalein, the tiny atoll in the Pacific where SpaceX launched the Falcon 1. Berger has reported on SpaceX for more than a decade, enjoying unparalleled journalistic access to the company’s inner workings. Liftoff is the culmination of these efforts, drawing upon exclusive interviews with dozens of former and current engineers, designers, mechanics, and executives, including Elon Musk. The enigmatic Musk, who founded the company with the dream of one day settling Mars, is the fuel that propels the book, with his daring vision for the future of space.Filled with never-before-told stories of SpaceX’s turbulent beginning, Liftoff is a saga of cosmic proportions.

    "His book is very compatible with XP. It is not about drawing pictures of a domain; it is about how you think of it, the language you use to talk about it, and how you organize your software to reflect your improving understanding of it. Eric thinks that learning about your problem domain is as likely to happen at the end of your project as at the beginning, and so refactoring is a big part of his technique. "The book is a fun read. Eric has lots of interesting stories, and he has a way with words. I see this book as essential reading for software developers--it is a future classic." --Ralph Johnson, author of Design Patterns "If you don't think you are getting value from your investment in object-oriented programming, this book will tell you what you've forgotten to do. "Eric Evans convincingly argues for the importance of domain modeling as the central focus of development and provides a solid framework and set of techniques for accomplishing it. This is timeless wisdom, and will hold up long after the methodologies du jour have gone out of fashion." --Dave Collins, author of Designing Object-Oriented User Interfaces "Eric weaves real-world experience modeling--and building--business applications into a practical, useful book. Written from the perspective of a trusted practitioner, Eric's descriptions of ubiquitous language, the benefits of sharing models with users, object life-cycle management, logical and physical application structuring, and the process and results of deep refactoring are major contributions to our field." --Luke Hohmann, author of Beyond Software Architecture "This book belongs on the shelf of every thoughtful software developer." --Kent Beck "What Eric has managed to capture is a part of the design process that experienced object designers have always used, but that we have been singularly unsuccessful as a group in conveying to the rest of the industry. We've given away bits and pieces of this knowledge...but we've never organized and systematized the principles of building domain logic. This book is important." --Kyle Brown, author of Enterprise Java(TM) Programming with IBM(R) WebSphere(R) The software development community widely acknowledges that domain modeling is central to software design. Through domain models, software developers are able to express rich functionality and translate it into a software implementation that truly serves the needs of its users. But despite its obvious importance, there are few practical resources that explain how to incorporate effective domain modeling into the software development process. Domain-Driven Design fills that need. This is not a book about specific technologies. It offers readers a systematic approach to domain-driven design, presenting an extensive set of design best practices, experience-based techniques, and fundamental principles that facilitate the development of software projects facing complex domains. Intertwining design and development practice, this book incorporates numerous examples based on actual projects to illustrate the application of domain-driven design to real-world software development. Readers learn how to use a domain model to make a complex development effort more focused and dynamic. A core of best practices and standard patterns provides a common language for the development team. A shift in emphasis--refactoring not just the code but the model underlying the code--in combination with the frequent iterations of Agile development leads to deeper insight into domains and enhanced communication between domain expert and programmer. Domain-Driven Design then builds on this foundation, and addresses modeling and design for complex systems and larger organizations.Specific topics covered include:Getting all team members to speak the same language Connecting model and implementation more deeply Sharpening key distinctions in a model Managing the lifecycle of a domain object Writing domain code that is safe to combine in elaborate ways Making complex code obvious and predictable Formulating a domain vision statement Distilling the core of a complex domain Digging out implicit concepts needed in the model Applying analysis patterns Relating design patterns to the model Maintaining model integrity in a large system Dealing with coexisting models on the same project Organizing systems with large-scale structures Recognizing and responding to modeling breakthroughs With this book in hand, object-oriented developers, system analysts, and designers will have the guidance they need to organize and focus their work, create rich and useful domain models, and leverage those models into quality, long-lasting software implementations.

    Dr. Schwartz presents a carefully designed program for getting the most out of your job, your marriage and family life, and your community. He proves that you don't need to be an intellectual or have innate talent to attain great success and satisfaction, but you do need to learn and understand the habit of thinking and behaving in ways that will get you there.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    No academic analysis or bystander’s account can capture it. Now Doug Edwards, Employee Number 59, offers the first inside view of Google, giving readers a chance to fully experience the bizarre mix of camaraderie and competition at this phenomenal company. Edwards, Google’s first director of marketing and brand management, describes it as it happened. We see the first, pioneering steps of Larry Page and Sergey Brin, the company’s young, idiosyncratic partners; the evolution of the company’s famously nonhierarchical structure (where every employee finds a problem to tackle or a feature to create and works independently); the development of brand identity; the races to develop and implement each new feature; and the many ideas that never came to pass. Above all, Edwards—a former journalist who knows how to write—captures the “Google Experience,” the rollercoaster ride of being part of a company creating itself in a whole new universe. I’m Feeling Lucky captures for the first time the unique, self-invented, yet profoundly important culture of the world’s most transformative corporation.

    Corporations & government agencies around the world are pouring billions into achieving AI’s Holy Grail—human-level intelligence. Once AI has attained it, scientists argue, it will have survival drives much like our own. We may be forced to compete with a rival more cunning, more powerful & more alien than we can imagine. Thru profiles of tech visionaries, industry watchdogs & groundbreaking AI systems, James Barrat's Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? Will they allow us to?

    A superbly practical book that explains what established businesses, public survey institutions, and new yentures have to know, have to learn, and have to do in today' s economy and marketplace.

     Plenty of experts argue that anyone who wants to develop a skill, play an instrument, or lead their field should start early, focus intensely, and rack up as many hours of deliberate practice as possible. If you dabble or delay, you'll never catch up to the people who got a head start. But a closer look at research on the world's top performers, from professional athletes to Nobel laureates, shows that early specialization is the exception, not the rule.David Epstein examined the world's most successful athletes, artists, musicians, inventors, forecasters and scientists. He discovered that in most fields--especially those that are complex and unpredictable--generalists, not specialists, are primed to excel. Generalists often find their path late, and they juggle many interests rather than focusing on one. They're also more creative, more agile, and able to make connections their more specialized peers can't see.Provocative, rigorous, and engrossing, Range makes a compelling case for actively cultivating inefficiency. Failing a test is the best way to learn. Frequent quitters end up with the most fulfilling careers. The most impactful inventors cross domains rather than deepening their knowledge in a single area. As experts silo themselves further while computers master more of the skills once reserved for highly focused humans, people who think broadly and embrace diverse experiences and perspectives will increasingly thrive.

    Yet, managing human beings and navigating complex product roadmaps is no easy task, and it's rare to find a product leader who can steward a digital product from concept to launch without a couple of major hiccups. Why do some product leaders succeed while others don't?This insightful book presents interviews with nearly 100 leading product managers from all over the world. Authors Richard Banfield, Martin Eriksson, and Nate Walkingshaw draw on decades of experience in product design and development to capture the approaches, styles, insights, and techniques of successful product managers. If you want to understand what drives good product leaders, this book is an irreplaceable resource.In three parts, Product Leadership helps you explore:Themes and patterns of successful teams and their leaders, and ways to attain those characteristicsThe best approaches for guiding your product team through the startup, emerging, and enterprise stages of a company's evolutionStrategies and tactics for working with customers, agencies, partners, and external stakeholders

    These insights may shake your assumptions, but they'll help you reach the "ah-ha!" moments that inspire truly great products.Validate or invalidate your hypothesis by talking to the right peopleLearn how to conduct successful customer interviews play-by-playDetect a customer's behaviors, pain points, and constraintsTurn interview insights into Minimum Viable Products to validate what customers will use and buyAdapt customer development strategies for large companies, conservative industries, and existing products

    Just as a single sick person can start an epidemic of the flu, so too can a small but precisely targeted push cause a fashion trend, the popularity of a new product, or a drop in the crime rate. This widely acclaimed bestseller, in which Malcolm Gladwell explores and brilliantly illuminates the tipping point phenomenon, is already changing the way people throughout the world think about selling products and disseminating ideas.Gladwell introduces us to the particular personality types who are natural pollinators of new ideas and trends, the people who create the phenomenon of word of mouth. He analyzes fashion trends, smoking, children's television, direct mail, and the early days of the American Revolution for clues about making ideas infectious, and visits a religious commune, a successful high-tech company, and one of the world's greatest salesmen to show how to start and sustain social epidemics.