Now in its third edition, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom Kyte and Darl Kuhn share a simple philosophy: ´´you can treat Oracle as a black box and just stick data into it, or you can understand how it works and exploit it as a powerful computing environment.´´ If you choose the latter, then you´ll find that there are few information management problems that you cannot solve quickly and elegantly. This fully revised third edition covers the developments up to Oracle Database 12 c . Significant new content is included surrounding Oracle´s new cloud feature set, and especially the use of pluggable databases. Each feature is taught in a proof-by-example manner, not only discussing what it is, but also how it works, how to implement software using it, and the common pitfalls associated with it. Don´t treat Oracle Database as a black-box. Get this book. Get under the hood. Turbo-charge your career. Revised to cover Oracle Database 12 c Proof-by-example approach: Let the evidence be your guide Dives deeply into Oracle Database´s most powerful features
Learn how to define strategies for cloud adoption of your Oracle database landscape. Understand private cloud, public cloud, and hybrid cloud computing in order to successfully design and manage databases in the cloud. The Cloud DBA-Oracle provides an overview of Database-as-a-Service (DBaaS) that you can use in defining your cloud adoption strategy. In-depth details of various cloud service providers for Oracle database are given, including Oracle Cloud and Amazon Web Services (AWS). Database administration techniques relevant to hosting databases in the cloud are shown in the book as well as the technical details needed to perform all database administration tasks and activities, such as migration to the cloud, backup in the cloud, and new database setup in the cloud. You will learn from real-world business cases and practical examples of administration of Oracle database in the cloud, highlighting the challenges faced and solutions implemented. What you will learn: Cloud computing concepts from the DBA perspective, such as private cloud, public cloud, hybrid cloud Technical details of all aspects of cloud database administration Challenges faced during setup of databases in private cloud or database migration to public cloud Key points to be kept in mind during database administration in the cloud Practical examples of successful Oracle database cloud migration and support Who Is This Book For All levels of IT professionals, from executives responsible for determining database strategies to database administrators and database architects who manage and design databases.
A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful First Edition, while adding a companion volume to take care of more specific requirements of different businesses. Each volume is accompanied by a CD-ROM, which is sold separately. Each CD-ROM provides powerful design templates discussed in the books in a ready-to-use electronic format, allowing companies and individuals to develop the databases they need at a fraction of the cost and a third of the time it would take to build them from scratch. Updating the data models from the First Edition CD-ROM, this resource allows database developers to quickly load a core set of data models and customize them to support a wide range of business functions.
Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christen´s book is divided into three parts: Part I, ´´Overview´´, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, ´´Steps of the Data Matching Process´´, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, ´´Further Topics´´, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.
This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics. Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies. This highly anticipated second edition has been thoroughly revised and expanded with new material on deep learning, graph models, mining social media, errors and pitfalls in big data evaluation, Twitter sentiment analysis, and dependency parsing discussion. The fully updated content also features in-depth discussions on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation. Features: includes chapter summaries and exercises; explores the application of each method; provides several case studies; contains links to free text-mining software.
Build mobile apps that specifically target your company´s unique business needs, with the same ease of writing a simple spreadsheet! With this book, you will build business apps designed to work with your company´s systems and databases, without having to enlist the expertise of costly, professionally trained software developers. In Beginning PowerApps, author and business applications expert Tim Leung guides you step-by-step through the process of building your own mobile app. He assumes no technical background, although if you have worked with Excel, you are one step closer. He guides you through scenarios, such as what to do if you have existing databases with complex data structures and how to write screens that can connect to those data. You will come away with an understanding of how to set up screen navigation, manipulate data from within apps, and write solutions to perform specific tasks. What You´ll Learn Connect with data Write formulas Visualize your data through charts Work with global positioning systems (GPS) Build flows Import and export data Manage offline scenarios Develop custom application programming interfaces (API) Who This Book Is For Beginners and non-developers, and assumes no prior knowledge of PowerApps
Learn Spring Boot and how to build Java-based enterprise, web, and microservice applications with it. In this book, you´ll see how to work with relational and NoSQL databases, build your first microservice, enterprise, or web application, and enhance that application with REST APIs. You´ll also learn how to build reactive web applications using Spring Boot along with Spring Web Reactive. Then you´ll secure your Spring Boot-created application or service before testing and deploying it. After reading and learning with Beginning Spring Boot 2 , you´ll have the skills and techniques to start building your first Spring Boot applications and microservices with confidence to take the next steps in your career journey. What You´ll Learn Use Spring Boot autoconfiguration Work with relational and NoSQL databases Build web applications with Spring Boot Apply REST APIs using Spring Boot Create reactive web applications using Spring Web Reactive Secure your Spring Boot applications or web services Test and deploy your Spring Boot applications Who This Book Is For Experienced Java and Spring Framework developers who are new to the new Spring Boot micro-framework.
An indispensable collection of practical tips and real-world advice for tackling common Python problems and taking your code to the next level. Features interviews with high-profile Python developers who share their tips, tricks, best practices, and real-world advice gleaned from years of experience. Sharpen your Python skills as you dive deep into the Python programming language with Serious Python. You´ll cover a range of advanced topics like multithreading and memorization, get advice from experts on things like designing APIs and dealing with databases, and learn Python internals to help you gain a deeper understanding of the language itself. Written for developers and experienced programmers, Serious Python brings together over 15 years of Python experience to teach you how to avoid common mistakes, write code more efficiently, and build better programs in less time. As you make your way through the book´s extensive tutorials, you´ll learn how to start a project and tackle topics like versioning, layouts, coding style, and automated checks. You´ll learn how to package your software for distribution, optimize performance, use the right data structures, define functions efficiently, pick the right libraries, build future-proof programs, and optimize your programs down to the bytecode. You´ll also learn how to: - Make and use effective decorators and methods, including abstract, static, and class methods - Employ Python for functional programming using generators, pure functions, and functional functions - Extend flake8 to work with the abstract syntax tree (AST) to introduce more sophisticated automatic checks into your programs - Apply dynamic performance analysis to identify bottlenecks in your code - Work with relational databases and effectively manage and stream data with PostgreSQL If you´ve been looking for a way to take your Python skills from good to great, Serious Python will help you get there. Learn from the experts and get seriously good at Python with Serious Python!