Database performance has become a major headache, and most IT departments believe that developers should provide simple SQL code to solve immediate problems and let DBAs tune any bad SQL later.In The Art of SQL, author and SQL expert Stephane Faroult argues that this safe approach only leads to disaster. His insightful book, named after Art of War by Sun Tzu, contends that writing quick inefficient code is sweeping the dirt under the rug. SQL code may run for 5 to 10 years, surviving several major releases of the database management system and on several generations of hardware. The code must be fast and sound from the start, and that requires a firm understanding of SQL and relational theory.The Art of SQL offers best practices that teach experienced SQL users to focus on strategy rather than specifics. Faroult's approach takes a page from Sun Tzu's classic treatise by viewing database design as a military campaign. You need knowledge, skills, and talent. Talent can't be taught, but every strategist from Sun Tzu to modern-day generals believed that it can be nurtured through the experience of others. They passed on their experience acquired in the field through basic principles that served as guiding stars amid the sound and fury of battle. This is what Faroult does with SQL.Like a successful battle plan, good architectural choices are based on contingencies. What if the volume of this or that table increases unexpectedly? What if, following a merger, the number of users doubles? What if you want to keep several years of data online? Faroult's way of looking at SQL performance may be unconventional and unique, but he's deadly serious about writing good SQL and using SQL well. The Art of SQL is not a cookbook, listing problems and giving recipes. The aim is to get you-and your manager-to raise good questions.

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    Its enable us to sense, measure, and understand aspects of our existence in ways never before possible. The Human Face of Big Data captures, in glorious photographs and moving essays, an extraordinary revolution sweeping, almost invisibly, through business, academia, government, healthcare, and everyday life. It's already enabling us to provide a healthier life for our children. To provide our seniors with independence while keeping them safe. To help us conserve precious resources like water and energy. To alert us to tiny changes in our health, weeks or years before we develop a life-threatening illness. To peer into our own individual genetic makeup. To create new forms of life.  And soon, as many predict, to re-engineer our own species. And we've barely scratched the surface . . . Over the past decade, Rick Smolan and Jennifer Erwitt, co-founders of Against All Odds Productions, have produced a series of ambitious global projects in collaboration with hundreds of the world's leading photographers, writers, and graphic designers. Their Day in the Life projects were credited for creating a mass market for large-format illustrated books (rare was the coffee table book without one).  Today their projects aim at sparking global conversations about emerging topics ranging from the Internet (24 Hours in Cyberspace), to Microprocessors (One Digital Day), to how the human race is learning to heal itself, (The Power to Heal) to the global water crisis (Blue Planet Run). This year Smolan and Erwitt dispatched photographers and writers in every corner of the globe to explore the world of “Big Data” and to determine if it truly does, as many in the field claim, represent a brand new toolset for humanity, helping address the biggest challenges facing our species. The book features 10 essays by noted writers:Introduction: OCEANS OF DATA by Dan GardnerChapter 1: REFLECTIONS IN A DIGITAL MIRROR by Juan Enriquez, CEO, BiotechnomomyChapter 2: OUR DATA OURSELVES by Kate Green, the EconomistChapter 3: QUANTIFYING MYSELF by AJ Jacobs, EsquireChapter 4: DARK DATA by Marc Goodman, Future Crime InstituteChapter 5:  THE SENTIENT SENSOR MESH by Susan Karlin, Fast CompanyChapter 6: TAKING THE PULSE OF THE PLANET by Esther Dyson, EDventureChapter 7: CITIZEN SCIENCE by Gareth Cook, the Boston GlobeChapter 8: A DEMOGRAPH OF ONE by Michael Malone, Forbes magazineChapter 9: THE ART OF DATA by Aaron Koblin, Google Artist in ResidenceChapter 10: DATA DRIVEN by Jonathan Harris, Cowbird The book will also feature stunning info graphics from NIGEL HOLMES.1) GOOGLING GOOGLE: all the ways Google uses Data to help humanity2) DATA IS THE NEW OIL3) THE WORLD ACCORDING TO TWITTER4) AUCTIONING EYEBALLS: The world of Internet advertising5) FACEBOOK: A Billion Friends

    In addition to changing how we live, these tools enable us to collect and process data about human behavior on a scale never before imaginable, offering entirely new approaches to core questions about social behavior. Bit by Bit is the key to unlocking these powerful methods--a landmark book that will fundamentally change how the next generation of social scientists and data scientists explores the world around us.Bit by Bit is the essential guide to mastering the key principles of doing social research in this fast-evolving digital age. In this comprehensive yet accessible book, Matthew Salganik explains how the digital revolution is transforming how social scientists observe behavior, ask questions, run experiments, and engage in mass collaborations. He provides a wealth of real-world examples throughout and also lays out a principles-based approach to handling ethical challenges.Bit by Bit is an invaluable resource for social scientists who want to harness the research potential of big data and a must-read for data scientists interested in applying the lessons of social science to tomorrow's technologies.Illustrates important ideas with examples of outstanding researchCombines ideas from social science and data science in an accessible style and without jargonGoes beyond the analysis of "found" data to discuss the collection of "designed" data such as surveys, experiments, and mass collaborationFeatures an entire chapter on ethicsIncludes extensive suggestions for further reading and activities for the classroom or self-study

    Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age.How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more.An essential introduction to the new technologies of digital currencyCovers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much moreFeatures an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slidesAlso suitable for use with the authors' Coursera online courseElectronic solutions manual (available only to professors)

     It is easy to be overwhelmed by the amount of information we encounter each day. Whether at work, at school, or in our personal endeavors, there’s a deepening (and inescapable) need for people to work with and understand information. Information architecture is the way that we arrange the parts of something to make it understandable as a whole. When we make things for others to use, the architecture of information that we choose greatly affects our ability to deliver our intended message to our users. We all face messes made of information and people. I define the word “mess” the same way that most dictionaries do: “A situation where the interactions between people and information are confusing or full of difficulties.” — Who doesn’t bump up against messes made of information and people every day? This book provides a seven step process for making sense of any mess. Each chapter contains a set of lessons as well as workbook exercises architected to help you to work through your own mess.

    Due to contractual restrictions, we reserve the right not to supply certain territories. Table of Contents Foreword Preface General Introduction Market Milk Special Milks Cream Butter Butteroil Ice Cream Cheese Condensed Milks Dried Milks Dried Milk Products Indian Dairy Products By-Products Appendices Index

    

    Readers learn how to reduce time constraints and develop programs efficiently by analyzing the feasibility of an algorithm before it is coded. The C++ language is brought up-to-date and simplified, and the Standard Template Library is now fully incorporated throughout the text. This Third Edition also features significantly revised coverage of lists, stacks, queues, and trees and an entire chapter dedicated to amortized analysis and advanced data structures such as the Fibonacci heap. Known for its clear and friendly writing style, Data Structures and Algorithm Analysis in C++ is logically organized to cover advanced data structures topics from binary heaps to sorting to NP-completeness. Figures and examples illustrating successive stages of algorithms contribute to Weiss' careful, rigorous and in-depth analysis of each type of algorithm.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    The approach is analytic and hands-on. The text uses interpreters, written in Scheme, to express the semantics of many essential language elements in a way that is both clear and directly executable. It also examines some important program analyses. Extensive exercises explore many design and implementation alternatives.

    You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google

    The book begins by introducing the R language, including the development environment. Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R.About the TechnologyR is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.About the BookR in Action is a language tutorial focused on practical problems. It presents useful statistics examples and includes elegant methods for handling messy, incomplete, and non-normal data that are difficult to analyze using traditional methods. And statistical analysis is only part of the story. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's InsidePractical data analysis, step by stepInterfacing R with other softwareUsing R to visualize dataOver 130 graphsEight reference appendixes================================Table of ContentsPart I Getting startedIntroduction to RCreating a datasetGetting started with graphsBasic data managementAdvanced data managementPart II Basic methodsBasic graphsBasic statisticsPart III Intermediate methodsRegressionAnalysis of variancePower analysisIntermediate graphsRe-sampling statistics and bootstrappingPart IV Advanced methodsGeneralized linear modelsPrincipal components and factor analysisAdvanced methods for missing dataAdvanced graphics

    They are now standard features in a wide range of languages and popular tools, including Perl, Python, Ruby, Java, VB.NET and C# (and any language using the .NET Framework), PHP, and MySQL.If you don't use regular expressions yet, you will discover in this book a whole new world of mastery over your data. If you already use them, you'll appreciate this book's unprecedented detail and breadth of coverage. If you think you know all you need to know about regularexpressions, this book is a stunning eye-opener.As this book shows, a command of regular expressions is an invaluable skill. Regular expressions allow you to code complex and subtle text processing that you never imagined could be automated. Regular expressions can save you time and aggravation. They can be used to craft elegant solutions to a wide range of problems. Once you've mastered regular expressions, they'll become an invaluable part of your toolkit. You will wonder how you ever got by without them.Yet despite their wide availability, flexibility, and unparalleled power, regular expressions are frequently underutilized. Yet what is power in the hands of an expert can be fraught with peril for the unwary. Mastering Regular Expressions will help you navigate the minefield to becoming an expert and help you optimize your use of regular expressions.Mastering Regular Expressions, Third Edition, now includes a full chapter devoted to PHP and its powerful and expressive suite of regular expression functions, in addition to enhanced PHP coverage in the central "core" chapters. Furthermore, this edition has been updated throughout to reflect advances in other languages, including expanded in-depth coverage of Sun's java.util.regex package, which has emerged as the standard Java regex implementation.Topics include:A comparison of features among different versions of many languages and toolsHow the regular expression engine worksOptimization (major savings available here!)Matching just what you want, but not what you don't wantSections and chapters on individual languagesWritten in the lucid, entertaining tone that makes a complex, dry topic become crystal-clear to programmers, and sprinkled with solutions to complex real-world problems, Mastering Regular Expressions, Third Edition offers a wealth information that you can put to immediateuse.Reviews of this new edition and the second edition: "There isn't a better (or more useful) book available on regular expressions."--Zak Greant, Managing Director, eZ Systems"A real tour-de-force of a book which not only covers the mechanics of regexes in extraordinary detail but also talks about efficiency and the use of regexes in Perl, Java, and .NET...If you use regular expressions as part of your professional work (even if you already have a good book on whatever language you're programming in) I would strongly recommend this book to you."--Dr. Chris Brown, Linux Format"The author does an outstanding job leading the reader from regexnovice to master. The book is extremely easy to read and chock full ofuseful and relevant examples...Regular expressions are valuable toolsthat every developer should have in their toolbox. Mastering RegularExpressions is the definitive guide to the subject, and an outstandingresource that belongs on every programmer's bookshelf. Ten out of TenHorseshoes."--Jason Menard, Java Ranch

    'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.