You d be up to your neck in normal forms before you even had a chance to wade. When Michael J. Hernandez needed a database design book to teach mere mortals like himself, there were none. So he began a personal quest to learn enough to write one. And he did.Now in its Second Edition, Database Design for Mere Mortals is a miracle for today s generation of database users who don t have the background -- or the time -- to learn database design the hard way. It s also a secret pleasure for working pros who are occasionally still trying to figure out what they were taught.Drawing on 13 years of database teaching experience, Hernandez has organized database design into several key principles that are surprisingly easy to understand and remember. He illuminates those principles using examples that are generic enough to help you with virtually any application.Hernandez s goals are simple. You ll learn how to create a sound database structure as easily as possible. You ll learn how to optimize your structure for efficiency and data integrity. You ll learn how to avoid problems like missing, incorrect, mismatched, or inaccurate data. You ll learn how to relate tables together to make it possible to get whatever answers you need in the future -- even if you haven t thought of the questions yet.If -- as is often the case -- you already have a database, Hernandez explains how to analyze it -- and leverage it. You ll learn how to identify new information requirements, determine new business rules that need to be applied, and apply them.Hernandez starts with an introduction to databases, relational databases, and the idea and objectives of database design. Next, you ll walk through the key elements of the database design process: establishing table structures and relationships, assigning primary keys, setting field specifications, and setting up views. Hernandez s extensive coverage of data integrity includes a full chapter on establishing business rules and using validation tables.Hernandez surveys bad design techniques in a chapter on what not to do -- and finally, helps you identify those rare instances when it makes sense to bend or even break the conventional rules of database design.There s plenty that s new in this edition. Hernandez has gone over his text and illustrations with a fine-tooth comb to improve their already impressive clarity. You ll find updates to reflect new advances in technology, including web database applications. There are expanded and improved discussions of nulls and many-to-many relationships; multivalued fields; primary keys; and SQL data type fields. There s a new Quick Reference database design flowchart. A new glossary. New review questions at the end of every chapter.Finally, it s worth mentioning what this book isn t. It isn t a guide to any specific database platform -- so you can use it whether you re running Access, SQL Server, or Oracle, MySQL or PostgreSQL. And it isn t an SQL guide. (If that s what you need, Michael J. Hernandez has also coauthored the superb SQL Queries for Mere Mortals). But if database design is what you need to learn, this book s worth its weight in gold. Bill CamardaBill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks for Dummies, Second Edition.

    My name's Frank Chimero. I've spent the better part of the last two years writing and speaking on design and thinking about the topics that orbit the practice: storytelling, concept, craft, and improvisation. I want to take all of the ideas I've had and connected these past few months and capture them in a book format.I've been teaching for the past 5 years, and I've always been a bit frustrated that there isn't a nice, concise book that overviews the mental state of a successful designer while they go through their creative process. For instance, many say that graphic design is visual communication. A cornerstone of communication is storytelling, and yet you'd be hard-pressed to find any discussion of how to tell stories with design in any design book. This should be remedied.There are new challenges in the world that need to be discussed, and I think design is a prime lens to consider these topics. As our world moves faster and as things become less stable, it becomes more important for individuals to embrace ambiguity, understand paradox, and realize that two things can conflict and still somehow both be true. We must realize that logic doesn't always work, and that sometimes nonsense is the best answer. These are the topics I intend to address in the book.The Shape of Design isn't going to be a text book. The project will be focused on Why instead of How. We have enough How; it's time for a thoughtful analysis of our practice and its characteristics so we can better practice our craft. After reading the book, I want you to look at what you do in a whole new light. Design is more than working for clients.But really, this book aims to look at the mindset and worldview that designing develops in order to answer one big, important question: How can we make things that help all of us live better?"

    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

    Learn about the components of a BI architecture, how to choose the appropriate tools and technologies, and how to roll out a BI strategy throughout the organisation.

    Users demand software that is well-behaved, good-looking, and easy to use. Your clients or managers demand originality and a short time to market. Your UI technology -- web applications, desktop software, even mobile devices -- may give you the tools you need, but little guidance on how to use them well.UI designers over the years have refined the art of interface design, evolving many best practices and reusable ideas. If you learn these, and understand why the best user interfaces work so well, you too can design engaging and usable interfaces with less guesswork and more confidence.Designing Interfaces captures those best practices as design patterns -- solutions to common design problems, tailored to the situation at hand. Each pattern contains practical advice that you can put to use immediately, plus a variety of examples illustrated in full color. You'll get recommendations, design alternatives, and warnings on when not to use them.Each chapter's introduction describes key design concepts that are often misunderstood, such as affordances, visual hierarchy, navigational distance, and the use of color. These give you a deeper understanding of why the patterns work, and how to apply them with more insight.A book can't design an interface for you -- no foolproof design process is given here -- but Designing Interfaces does give you concrete ideas that you can mix and recombine as you see fit. Experienced designers can use it as a sourcebook of ideas. Novice designers will find a roadmap to the world of interface and interaction design, with enough guidance to start using these patterns immediately.

    With this practical book, you'll explore the often-misunderstood practice of user story mapping, and learn how it can help keep your team stay focused on users and their experience throughout the development process.You and your team will learn that user stories aren't a way to write better specifications, but a way to organize and have better conversations. This book will help you understand what kinds of conversations you should be having, when to have them, and what to keep track of when you do. Learn the key concepts used to create a great story map. Understand how user stories really work, and how to make good use of them in agile and lean projects. Examine the nuts and bolts of managing stories through the development cycle. Use strategies that help you continue to learn before and after the product's release to customers and usersUser Story Mapping is ideal for agile and lean software development team members, product managers and UX practitioners in commercial product companies, and business analysts and project managers in IT organizations—whether you're new to this approach or want to understand more about it.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them

    Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you're ready to get started.Use R's default graphics for quick exploration of dataCreate a variety of bar graphs, line graphs, and scatter plotsSummarize data distributions with histograms, density curves, box plots, and other examplesProvide annotations to help viewers interpret dataControl the overall appearance of graphicsRender data groups alongside each other for easy comparisonUse colors in plotsCreate network graphs, heat maps, and 3D scatter plotsStructure data for graphing

    The range covered reflects the breadth of design, from hardware and software design, to architecture and Formula One. The book offers new insights and understanding of design thinking, based on evidence from observation and investigation of design practice. Author Nigel Cross, considered one of design's most influential thinkers, goes to the heart of what it means to think and work as a designer. The book is an ideal guide for anyone who wants to be a designer or to know how good designers work in the field of contemporary design.

    So while the focus is on design, the approach is holistic. Hence, the book speaks to designers, usability specialists, the HCI community, product managers, and business executives. There is an emphasis on balancing the back-end concern with usability and engineering excellence (getting the design right) with an up-front investment in sketching and ideation (getting the right design). Overall, the objective is to build the notion of informed design: molding emerging technology into a form that serves our society and reflects its values.Grounded in both practice and scientific research, Bill Buxton s engaging work aims to spark the imagination while encouraging the use of new techniques, breathing new life into user experience design. Covers sketching and early prototyping design methods suitable for dynamic product capabilities: cell phones that communicate with each other and other embedded systems, "smart" appliances, and things you only imagine in your dreamsThorough coverage of the design sketching method which helps easily build experience prototypes-without the effort of engineering prototypes which are difficult to abandonReaches out to a range of designers, including user interface designers, industrial designers, software engineers, usability engineers, product managers, and othersFull of case studies, examples, exercises, and projects, and access to video clips that demonstrate the principles and methods"

    You'd like to learn how to do more work with SQL inside the database before pushing data across the network to your applications. You'd like to take your SQL skills to the next level.Let's face it, SQL is a deceptively simple language to learn, and many database developers never go far beyond the simple statement: SELECT columns FROM table WHERE conditions. But there is so much more you can do with the language. In the SQL Cookbook, experienced SQL developer Anthony Molinaro shares his favorite SQL techniques and features. You'll learn about:Window functions, arguably the most significant enhancement to SQL in the past decade. If you're not using these, you're missing outPowerful, database-specific features such as SQL Server's PIVOT and UNPIVOT operators, Oracle's MODEL clause, and PostgreSQL's very useful GENERATE_SERIES functionPivoting rows into columns, reverse-pivoting columns into rows, using pivoting to facilitate inter-row calculations, and double-pivoting a result setBucketization, and why you should never use that term in Brooklyn.How to create histograms, summarize data into buckets, perform aggregations over a moving range of values, generate running-totals and subtotals, and other advanced, data warehousing techniquesThe technique of walking a string, which allows you to use SQL to parse through the characters, words, or delimited elements of a stringWritten in O'Reilly's popular Problem/Solution/Discussion style, the SQL Cookbook is sure to please. Anthony's credo is: When it comes down to it, we all go to work, we all have bills to pay, and we all want to go home at a reasonable time and enjoy what's still available of our days. The SQL Cookbook moves quickly from problem to solution, saving you time each step of the way.

    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

    In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems.From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it.Among the many topics covered, you’ll discover how to:Test drive your data to see if it’s ready for analysisWork spreadsheet data into a usable formHandle encoding problems that lurk in text dataDevelop a successful web-scraping effortUse NLP tools to reveal the real sentiment of online reviewsAddress cloud computing issues that can impact your analysis effortAvoid policies that create data analysis roadblocksTake a systematic approach to data quality analysis

    Consultant Brown describes the ten basic deliverables as belonging to three basic types, thereby making it much easier to sort out who gets what and when. He wo