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The only Oracle Press guide to MySQL Workbench explains how to design and model MySQL databases. MySQL Workbench Data Modeling and Development helps developers learn how to effectively use this powerful product for database modeling, reverse engineering, and interaction with the database without writing SQL statements. MySQL Workbench is a graphical user interface that can be used to create and maintain MySQL databases without coding. The book covers the interface and explains how to accomplish each step by illustrating best practices visually. Clear examples, instructions, and explanations reveal, in a single volume, the art of database modeling. This Oracle Press guide shows you how to get the tool to do what you want. Annotated screen shots demonstrate all interactions with the tool, and text explains the how, what, and why of each step. Complete coverage Installation and Configuration; Creating and Managing Connections; Data Modeling Concepts; Creating an ERD; Defining the Physical Schemata; Creating and Managing Tables; Creating and Managing Relationships; Creating and Managing Views; Creating and Managing Routines; Creating and Managing Routine Groups; Creating and Managing User & Groups; Creating and Managing SQL Scripts; Generating SQL Scripts; Forward Engineering a Data Model; Synchronize a Model with a Database; Reverse Engineering a Database; Managing Differences in the Data Catalog; Creating and Managing Model Notes; Editing Table Data; Editing Generated Scripts; Creating New Instances; Managing Import and Export; Managing Security; Managing Server Instances
Many professionals and students in engineering, science, business, and other application fields need to develop Windows-based and web-enabled information systems to store and use data for decision support, without help from professional programmers. However, few books are available to train professionals and students who are not professional programmers to develop these information systems. Developing Windows-Based and Web-Enabled Information Systems fills this gap, providing a self-contained, easy-to-understand, and well-illustrated text that explores current concepts, methods, and software tools for developing Windows-based and web-enabled information systems. Written in an easily accessible style, the book details current concepts, methods, and software tools for Windows-based and web-enabled information systems that store and use data. It is self-contained with easy-to-understand small examples to walk through concepts and implementation details along with large-scale case studies. The book describes data modeling methods including entity–relationship modeling, relational modeling and normalization, and object-oriented data modeling, to develop data models of a database. The author covers how to use software tools in the Microsoft application development environment, including Microsoft Access, MySQL, SQL, Visual Studio, Visual Basic, VBA, HTML, and XML, to implement databases and develop Windows-based and web-enabled applications with the database, graphical user interface, and program components. The book takes you through the entire process of developing a computer and network application for an information system, highlighting concepts and operation details. In each chapter, small data examples are used to manually walk through concepts and operational details. These features and more give you the conceptual understanding and practical skill required, even if you don’t have a computer science background, to develop Windows-based or web-enabled applications for your specialized information system.
Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery. Written for health care professionals and executives, this is not a technical book on the use of statistics and machine-learning algorithms for extracting knowledge out of data, nor a book on the intricacies of database design. Instead, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, this book is accessible to health care professionals who might not have an IT and analytics background. It includes case studies that illustrate the business processes underlying the use of big data and health analytics to improve health care delivery. Highlighting lessons learned from the case studies, the book supplies readers with the foundation required for further specialized study in health analytics and data management. Coverage includes community health information, information visualization which offers interactive environments and analytic processes that support exploration of EHR data, the governance structure required to enable data analytics and use, federal regulations and the constraints they place on analytics, and information security. Links to websites, videos, articles, and other online content that expand and support the primary learning objectives for each major section of the book are also included to help you develop the skills you will need to achieve quality improvements in health care delivery through the effective use of data and analytics.
Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling statistical questions. Contemporary data science requires a tight integration of knowledge from statistics, computer science, mathematics, and a domain of application. This book will help readers with some background in statistics and modest prior experience with coding develop and practice the appropriate skills to tackle complex data science projects. The book features a number of exercises and has a flexible organization conducive to teaching a variety of semester courses.
Introduction to Health Informatics is the first book to examine health informatics within the Canadian healthcare environment. Presenting concepts and applications of health informatics in a clear and structured way, the author considers key foundational topics including computers and networks, databases and information systems, system analysis and design, and usability. After introducing students to the building blocks of the field, Christo El Morr explores information systems in hospitals, telemedicine, consumer health informatics, public health informatics, and electronic health records. The text wraps up with a discussion of privacy, confidentiality, security challenges, and emerging trends such as big data analytics, gamification, and wearable devices. The chapters present a wealth of learning tools, including key terms, questions that test the reader’s understanding, reflective activities, and practical assignments that make use of free software. Shedding light on current issues and the intricacies involved in health informatics in Canada, each chapter provides examples of provincial and territorial projects and features an interview with a health informatics professional about real-life applications. Identifying how information technologies influence and affect a range of Canadian healthcare stakeholders, this comprehensive overview is an invaluable read for students in the health informatics, health management, health policy, and global health fields.

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