Database Systems With Case Studies

Database Systems with Case Studies, covers exactly what students needs to know in an introductory database system course. This book focuses on database design and exposes students to a variety of approaches for getting the Data Model right. The book addresses issues related to database performance (Query Processing) and Transaction Management for multi-user environments. This book also introduces non-relational XML format to students. The approach taken to teach the topics is through introduction of many real-world enterprise database case studies and practice problems. The case studies are selected based on modern application areas, keeping the student’s interest in mind. The book provides hands-on experience of database design issues with several ready-made lab exercises. For grading students’ understanding of the topics, several challenging assignments are also provided at the end of chapters. Multiple-choice self-tests are provided for formative assessment throughout the book. The book is suitable for the undergraduate students of Computer Science and Engineering, Information Technology, and students of Computer Applications (BCA/MCA). Key features • All the topics are illustrated with practical examples. • Topics like Entity-Relationship diagram (ERD), are discussed with Diagrams and Visual Aids. • Students are exposed to the various approaches for determining data requirements. • Structured Query Language (SQL) examples are worked with scripts, results and solutions. • Exclusive lab exercises on SQL, can be used as assignments.

A breakthrough sourcebook to the challenges and solutions for mobile database systems This text enables readers to effectively manage mobile database systems (MDS) and data dissemination via wireless channels. The author explores the mobile communication platform and analyzes its use in the development of a distributed database management system. Workable solutions for key challenges in wireless information management are presented throughout the text. Following an introductory chapter that includes important milestones in the history and development of mobile data processing, the text provides the information, tools, and resources needed for MDS management, including: * Fundamentals of wireless communication * Location and handoff management * Fundamentals of conventional database management systems and why existing approaches are not adequate for mobile databases * Concurrency control mechanism schemes * Data processing and mobility * Management of transactions * Mobile database recovery schemes * Data dissemination via wireless channels Case studies and examples are used liberally to aid in the understanding and visualization of complex concepts. Various exercises enable readers to test their grasp of each topic before advancing in the text. Each chapter also concludes with a summary of key concepts as well as references for further study. Professionals in the mobile computing industry, particularly e-commerce, will find this text indispensable. With its extensive use of case studies, examples, and exercises, it is also highly recommended as a graduate-level textbook.

Modern biological databases comprise not only data, but also sophisticated query facilities and bioinformatics data analysis tools. This book provides an exploration through the world of Bioinformatics Database Systems. The book summarizes the popular and innovative bioinformatics repositories currently available, including popular primary genetic and protein sequence databases, phylogenetic databases, structure and pathway databases, microarray databases and boutique databases. It also explores the data quality and information integration issues currently involved with managing bioinformatics databases, including data quality issues that have been observed, and efforts in the data cleaning field. Biological data integration issues are also covered in-depth, and the book demonstrates how data integration can create new repositories to address the needs of the biological communities. It also presents typical data integration architectures employed in current bioinformatics databases. The latter part of the book covers biological data mining and biological data processing approaches using cloud-based technologies. General data mining approaches are discussed, as well as specific data mining methodologies that have been successfully deployed in biological data mining applications. Two biological data mining case studies are also included to illustrate how data, query, and analysis methods are integrated into user-friendly systems. Aimed at researchers and developers of bioinformatics database systems, the book is also useful as a supplementary textbook for a one-semester upper-level undergraduate course, or an introductory graduate bioinformatics course.

The second edition of this bestselling title is a perfect blend of theoretical knowledge and practical application. It progresses gradually from basic to advance concepts in database management systems, with numerous solved exercises to make learning easier and interesting. New to this edition are discussions on more commercial database management systems.

The field of data mining provides techniques for automated discovery of valuable information from the accumulated data of computerized operations of enterprises. This book offers a clear and comprehensive introduction to both data mining theory and practice. It is written primarily as a textbook for the students of computer science, management, computer applications, and information technology. The book ensures that the students learn the major data mining techniques even if they do not have a strong mathematical background. The techniques include data pre-processing, association rule mining, supervised classification, cluster analysis, web data mining, search engine query mining, data warehousing and OLAP. To enhance the understanding of the concepts introduced, and to show how the techniques described in the book are used in practice, each chapter is followed by one or two case studies that have been published in scholarly journals. Most case studies deal with real business problems (for example, marketing, e-commerce, CRM). Studying the case studies provides the reader with a greater insight into the data mining techniques. The book also provides many examples, review questions, multiple choice questions, chapter-end exercises and a good list of references and Web resources especially those which are easy to understand and useful for students. A number of class projects have also been included.

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

This book discusses in detail a series of examples drawn from scholarly projects that use the OCHRE database platform (Online Cultural and Historical Research Environment). These case studies illustrate the wide range of data that can be managed with this platform and the wide variety of problems solved by OCHRE’s item-based graph data model. The unique features and design principles of the OCHRE platform are explained and justified, helping readers to imagine how the system could be used for their own data. Data generated by studies in the humanities and social sciences is often semi-structured, fragmented, highly variable, and subject to many interpretations, making it difficult to represent adequately in a conventional database. The authors examine commonly used methods of data management in the humanities and offer a compelling argument for a different approach that takes advantage of powerful computational techniques for organizing scholarly information. This book is a challenge to scholars in the humanities and social sciences, asking them to expect more from technology as they pursue their research goals. Written jointly by a software engineer and a research scholar, each with many years of experience in applying database methods to diverse kinds of scholarly data, it shows how scholars can make the most of their existing data while going beyond the limitations of commonly used software tools to represent their objects of study in a more accurate, nuanced, and flexible way.

Dalam dunia bisnis modern sekarang ini, teknologi informasi memegang peranan yang sangat penting dalam perekonomian dunia. Kebanyakan perusahaan menganggap teknologi informasi sebagai jalan keluar untuk mengatasi permasalahan-permasalahan yang timbul. Selain itu, dalam era globalisasi sekarang ini, kebutuhan akan informasi merupakan suatu titik vital yang sangat penting. Tak ketinggalan pula peranan basis data dalam hal tersebut. Tanpa basis data, teknologi informasi tidak akan berarti apa-apa dalam suatu perusahaan. Buku ini disusun dengan tujuan memberikan kemudahan bagi Anda untuk membuat sintaks-sintaks SQL Data Definition Language, SQL Data Manipulation Language, dan Akses Kontrol. Cocok digunakan para mahasiswa yang mengambil mata kuliah Sistem Basis Data khususnya, serta masyarakat Indonesia yang berminat mempelajari basis data umumnya. Ditujukan pula bagi kita yang akan dan tengah berkecimpung dalam dunia IT, baik dalam bidang programming maupun dalam bidang basis data, di mana memiliki tekad sungguh-sungguh akan mempelajari bagaimana merancang basis data yang benar dan baik. Penyajian materi diberikan secara jelas dan terperinci disertai dengan berbagai contoh kasus nyata sehari-hari. Dalam setiap bab diberikan contoh-contoh latihan dan diakhiri dengan soal latihan yang dapat membantu Anda untuk lebih memahami ulasan yang telah disajikan. Pembahasan dalam buku ini mencakup: - Introduction to Databases - Database Environment - Relational Algebra and Relational Calculus - Database Architectures and the Web - The Relational Model - SQL – Data Manipulation & Data Definition - Advanced SQL - Security and Administration - Transaction Management - Database System Development Lifecycle - Database Analysis & Normalization - Advanced Normalization - Entity Relationship (ER) Modelling - Enhanced Entity-Relationship Modelling - Distributed DBMSs – Concept and Design - Data Warehousing Concepts - Data Mining & Source Code