Updated to include two extended final chapters with in-depth prescriptions for building a career in advertising, this edition also features a real-world look at the day-to-day operations of today's ad agencies. Among the most disparaged campaigns in advertising history, the Mr. Whipple ads for Charmin toilet paper were also wildly successful. Sullivan explores the Whipple phenomenon, examining why bad ads sometimes work, why great ads sometimes fail, and how advertisers can learn to balance creative work with the mandate to sell products.

    But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You'll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization's goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures

    It illustrates little-known features and techniques for getting the most from the Tableau toolset, supporting the needs of the business analysts who use the product as well as the data and IT managers who support it.This comprehensive guide covers the core feature set for data analytics, illustrating best practices for creating and sharing specific types of dynamic data visualizations. Featuring a helpful full-color layout, the book covers analyzing data with Tableau Desktop, sharing information with Tableau Server, understanding Tableau functions and calculations, and Use Cases for Tableau Software.Includes little-known, as well as more advanced features and techniques, using detailed, real-world case studies that the author has developed as part of his consulting and training practice Explains why and how Tableau differs from traditional business information analysis tools Shows you how to deploy dashboards and visualizations throughout the enterprise Provides a detailed reference resource that is aimed at users of all skill levels Depicts ways to leverage Tableau across the value chain in the enterprise through case studies that target common business requirements Endorsed by Tableau Software Tableau Your Data shows you how to build dynamic, best-of-breed visualizations using the Tableau Software toolset.

    The Song Machine goes behind the scenes to offer an insider’s look at the global hit factories manufacturing the songs that have everyone hooked. Full of vivid, unexpected characters—alongside industry heavy-hitters like Katy Perry, Rihanna, Max Martin, and Ester Dean—this fascinating journey into the strange world of pop music reveals how a new approach to crafting smash hits is transforming marketing, technology, and even listeners’ brains. You’ll never think about music the same way again.A Wall Street Journal Best Business Book

    Something as simple as color choices can render a product unusable for millions. These mismatches are the building blocks of exclusion. In Mismatch, Kat Holmes describes how design can lead to exclusion, and how design can also remedy exclusion. Inclusive design methods--designing objects with rather than for excluded users--can create elegant solutions that work well and benefit all.Holmes tells stories of pioneers of inclusive design, many of whom were drawn to work on inclusion because of their own experiences of exclusion. A gamer and designer who depends on voice recognition shows Holmes his "Wall of Exclusion," which displays dozens of game controllers that require two hands to operate; an architect shares her firsthand knowledge of how design can fail communities, gleaned from growing up in Detroit's housing projects; an astronomer who began to lose her eyesight adapts a technique called "sonification" so she can "listen" to the stars.Designing for inclusion is not a feel-good sideline. Holmes shows how inclusion can be a source of innovation and growth, especially for digital technologies. It can be a catalyst for creativity and a boost for the bottom line as a customer base expands. And each time we remedy a mismatched interaction, we create an opportunity for more people to contribute to society in meaningful ways.

    Artists use these journals to document their daily lives, produce their initial ideas for bigger projects, and practice their skills. Using a variety of media from paint to pencil to collage, these pages can become works of art themselves. They often feel fresh and alive because they are first thoughts and often not reworked. These pages capture the artist's personalities along with glimpses of their process of working and inspirations.In Drawn In, you can take a peek inside the sketchbooks of 44 high-profile, amazingly talented artists as they discuss their collections and how they use them. Featuring a spectrum of creators from illustrators and fine artists to graphic designers and cartoonists, this books offers an inside, full-color glimpse into pages filled with pencil and pen sketches, thumbnail drawings, unpublished comics, elaborate collages, loose clippings, and much more. Become inspired by these incredible artists and the pages they share in Drawn In!

    Photographs, illustrations, screen shots, and images of 3D models are included for each project.This unique resource emphasizes using off-the-shelf components, readily available materials, and accessible fabrication techniques. Simple projects give you hands-on practice applying the skills covered in each chapter, and more complex projects at the end of the book incorporate topics from multiple chapters. Turn your imaginative ideas into reality with help from this practical, inventive guide.Discover how to:Find and select materialsFasten and join partsMeasure force, friction, and torqueUnderstand mechanical and electrical power, work, and energyCreate and control motionWork with bearings, couplers, gears, screws, and springsCombine simple machines for work and funProjects include:Rube Goldberg breakfast machineMousetrap powered carDIY motor with magnet wireMotor direction and speed controlDesigning and fabricating spur gearsAnimated creations in paperAn interactive rotating platformSmall vertical axis wind turbineSADbot: the seasonally affected drawing robotMake Great Stuff!TAB, an imprint of McGraw-Hill Professional, is a leading publisher of DIY technology books for makers, hackers, and electronics hobbyists.

    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""

    We're rebelling against technology that's too complicated, DVD players with too many menus, and software accompanied by 75-megabyte "read me" manuals. The iPod's clean gadgetry has made simplicity hip. But sometimes we find ourselves caught up in the simplicity paradox: we want something that's simple and easy to use, but also does all the complex things we might ever want it to do. In The Laws of Simplicity, John Maeda offers ten laws for balancing simplicity and complexity in business, technology, and design—guidelines for needing less and actually getting more.Maeda—a professor in MIT's Media Lab and a world-renowned graphic designer—explores the question of how we can redefine the notion of "improved" so that it doesn't always mean something more, something added on.Maeda's first law of simplicity is "Reduce." It's not necessarily beneficial to add technology features just because we can. And the features that we do have must be organized (Law 2) in a sensible hierarchy so users aren't distracted by features and functions they don't need. But simplicity is not less just for the sake of less. Skip ahead to Law 9: "Failure: Accept the fact that some things can never be made simple." Maeda's concise guide to simplicity in the digital age shows us how this idea can be a cornerstone of organizations and their products—how it can drive both business and technology. We can learn to simplify without sacrificing comfort and meaning, and we can achieve the balance described in Law 10. This law, which Maeda calls "The One," tells us: "Simplicity is about subtracting the obvious, and adding the meaningful."

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    We all need to know what it is and how it works - that much is obvious. But is a basic understanding of the theory enough to hold your own in strategy meetings? Probably. But what will set you apart from the rest is actually knowing how to USE big data to get solid, real-world business results - and putting that in place to improve performance. Big Data will give you a clear understanding, blueprint, and step-by-step approach to building your own big data strategy. This is a well-needed practical introduction to actually putting the topic into practice. Illustrated with numerous real-world examples from a cross section of companies and organisations, Big Data will take you through the five steps of the SMART model: Start with Strategy, Measure Metrics and Data, Apply Analytics, Report Results, Transform. Discusses how companies need to clearly define what it is they need to know Outlines how companies can collect relevant data and measure the metrics that will help them answer their most important business questions Addresses how the results of big data analytics can be visualised and communicated to ensure key decisions-makers understand them Includes many high-profile case studies from the author's work with some of the world's best known brands

    Lessig reveals the solutions to this impasse offered by a collaborative yet profitable “hybrid economy”.Lawrence Lessig, the reigning authority on intellectual property in the Internet age, spotlights the newest and possibly the most harmful culture war—a war waged against our kids and others who create and consume art. America’s copyright laws have ceased to perform their original, beneficial role: protecting artists’ creations while allowing them to build on previous creative works. In fact, our system now criminalizes those very actions. For many, new technologies have made it irresistible to flout these unreasonable and ultimately untenable laws. Some of today’s most talented artists are felons, and so are our kids, who see no reason why they shouldn’t do what their computers and the Web let them do, from burning a copyrighted CD for a friend to “biting” riffs from films, videos, songs, etc and making new art from them.Criminalizing our children and others is exactly what our society should not do, and Lessig shows how we can and must end this conflict—a war as ill conceived and unwinnable as the war on drugs. By embracing “read-write culture,” which allows its users to create art as readily as they consume it, we can ensure that creators get the support—artistic, commercial, and ethical—that they deserve and need. Indeed, we can already see glimmers of a new hybrid economy that combines the profit motives of traditional business with the “sharing economy” evident in such Web sites as Wikipedia and YouTube. The hybrid economy will become ever more prominent in every creative realm—from news to music—and Lessig shows how we can and should use it to benefit those who make and consume culture.Remix is an urgent, eloquent plea to end a war that harms our children and other intrepid creative users of new technologies. It also offers an inspiring vision of the post-war world where enormous opportunities await those who view art as a resource to be shared openly rather than a commodity to be hoarded.

    Gigabytes, exabytes (that’s one quintillion bytes) of data are sitting on servers across the world. So how can we start to access this explosion of information, this “big data,” and what can it tell us?   Erez Aiden and Jean-Baptiste Michel are two young scientists at Harvard who started to ask those questions. They teamed up with Google to create the Ngram Viewer, a Web-based tool that can chart words throughout the massive Google Books archive, sifting through billions of words to find fascinating cultural trends. On the day that the Ngram Viewer debuted in 2010, more than one million queries were run through it.   On the front lines of Big Data, Aiden and Michel realized that this big dataset—the Google Books archive that contains remarkable information on the human experience—had huge implications for looking at our shared human history. The tool they developed to delve into the data has enabled researchers to track how our language has evolved over time, how art has been censored, how fame can grow and fade, how nations trend toward war. How we remember and how we forget. And ultimately, how Big Data is changing the game for the sciences, humanities, politics, business, and our culture.

    Freed from the rigorous constraints of designing for real users, sci-fi production designers develop blue-sky interfaces that are inspiring, humorous, and even instructive. By carefully studying these "outsider" user interfaces, designers can derive lessons that make their real-world designs more cutting edge and successful.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data