Explains what you need to know to successfully implement the stewardship portion of data governance, including how to organize, train, and work with data stewards, get high-quality business definitions and other metadata, and perform the day-to-day tasks using a minimum of the steward´s time and effort.
This book teaches test managers advanced skills in test estimation, test planning, test monitoring, and test control. Readers will learn how to define the overall testing goals and strategies for the systems being tested. This hands-on, exercise-rich book provides experience with planning, scheduling, and tracking these tasks. You´ll learn to describe and organize necessary activities, as well as to select, acquire, and assign adequate resources for testing tasks, and how to form, organize, and lead testing teams. You´ll master the organization of communication among team members and between the testing teams, and other stakeholders. Additionally, you´ll learn how to justify decisions and provide adequate reporting information where applicable. With over 30 years of software and systems engineering experience, author Rex Black is President of RBCS, a leader in software, hardware, and systems testing. Rex is the most prolific author practicing in the field of software testing today. He has published a dozen books on testing that have sold tens of thousands of copies worldwide. He is past president of the International Software Testing Qualifications Board (ISTQB) and a director of the American Software Testing Qualifications Board (ASTQB). This second edition has been thoroughly updated to reflect the new ISTQB Advanced Test Manager 2012 Syllabus, and the latest ISTQB Glossary. Rex Black is one of the main participants in the ISTQB Advanced Level Working Group, and his edition reflects his unique insights into these changes. This book will help you prepare for the ISTQB Advanced Test Manager exam. Included are sample exam questions, at the appropriate level of difficulty, for most of the learning objectives covered by the ISTQB Advanced Level Syllabus. The ISTQB certification program is the leading software tester certification program in the world. With about 350,000 certificate holders and a global presence in over 50 countries, you can be confident in the value and international stature that the Advanced Test Manager certificate can offer you.
The CCNA Wireless Official Cert Guide is a comprehensive self-study tool for preparing for the latest CCNA Wireless exam. Complete coverage of all exam topics as posted on the exam topic blueprint ensures readers will arrive at a thorough understanding of what they need to master to succeed on the exam. The book follows a logical organization of the CCNA Wireless exam objectives. Material is presented in a concise manner, focusing on increasing readers´ retention and recall of exam topics. Readers will organize their exam preparation through the use of the consistent features in these chapters.
Despite growing interest in the mathematical analysis of algorithms, basic information on methods and models has rarely been directly accessible to practitioners, researchers, or students. This book organizes and presents that knowledge, fully introducing today´s primary techniques for mathematically analyzing algorithms. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematical and computer science material, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They focus on ´´average-case´´ or ´´probabilistic´´ analysis, while also covering tools for ´´worst case´´ or ´´complexity´´ analysis. Improvements in this edition include: * Upgraded figures and code * Newer style for presenting much of the text´s math * An all-new chapter on trees This book´s thorough, self-contained coverage will help readers appreciate the field´s challenges, prepare them for advanced results covered in Donald Knuth´s books, and provide the background they need to keep abreast of new research. Coverage includes: recurrences, generating functions, asymptotics, trees, strings, maps, sorting, tree search, string search, and hashing algorithms. Ideal for junior- or senior-level courses on mathematical analysis of algorithms, this book will also be useful in courses on discrete mathematics for computer scientists, and in introducing mathematics students to computer science principles related to algorithms and data structures. Product Description Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Authors Robert Sedgewick and the late Philippe Flajolet emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Improvements and additions in this new edition include upgraded figures and code, an all-new chapter introducing analytic combinatorics, and simplified derivations via analytic combinatorics throughout. The book´s thorough, self-contained coverage will help readers appreciate the field´s challenges and prepare them for advanced study.
Build server-side applications more efficiently?and improve your PHP programming skills in the process?by learning how to use design patterns in your code. This book shows you how to apply several object-oriented patterns through simple examples, and demonstrates many of them in full-fledged working applications. Learn how these reusable patterns help you solve complex problems, organize object-oriented code, and revise a big project by only changing small parts. With Learning PHP Design Patterns, you?ll learn how to adopt a more sophisticated programming style and dramatically reduce development time. * Learn design pattern concepts, including how to select patterns to handle specific problems * Get an overview of object-oriented programming concepts such as composition, encapsulation, polymorphism, and inheritance * Apply creational design patterns to create pages dynamically, using a factory method instead of direct instantiation * Make changes to existing objects or structure without having to change the original code, using structural design patterns * Use behavioral patterns to help objects work together to perform tasks * Interact with MySQL, using behavioral patterns such as Proxy and Chain of Responsibility * Explore ways to use PHP?s built-in design pattern interfaces
´´Eric Evans has written a fantastic book on how you can make the design of your software match your mental model of the problem domain you are addressing. ´´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® WebSphere® 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-Dr
Prepare for Microsoft Exam 70-761?and help demonstrate your real-world mastery of SQL Server 2016 Transact-SQL data management, queries, and database programming. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical-thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: ? Filter, sort, join, aggregate, and modify data ? Use subqueries, table expressions, grouping sets, and pivoting ? Query temporal and non-relational data, and output XML or JSON ? Create views, user-defined functions, and stored procedures ? Implement error handling, transactions, data types, and nulls This Microsoft Exam Ref: ? Organizes its coverage by exam objectives ? Features strategic, what-if scenarios to challenge you ? Assumes you have experience working with SQL Server as a database administrator, system engineer, or developer ? Includes downloadable sample database and code for SQL Server 2016 SP1 (or later) and Azure SQL Database
Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto. Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists both contributing expertise in their respective fields, communication alone can be a challenge. Agile Machine Learning teaches you how to deliver superior data products through agile processes and to learn, by example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment. The authors´ approach models the ground-breaking engineering principles described in the Agile Manifesto. The book provides further context, and contrasts the original principles with the requirements of systems that deliver a data product. What You´ll Learn Effectively run a data engineering team that is metrics-focused, experiment-focused, and data-focused Make sound implementation and model exploration decisions based on the data and the metrics Know the importance of data wallowing: analyzing data in real time in a group setting Recognize the value of always being able to measure your current state objectively Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations Who This Book Is For Anyone who manages a machine learning team, or is responsible for creating production-ready inference components. Anyone responsible for data project workflow of sampling data; labeling, training, testing, improving, and maintaining models; and system and data metrics will also find this book useful. Readers should be familiar with software engineering and understand the basics of machine learning and working with data.