The book is intended to provide an insight into the DBMS concepts. An effort has been made to familiarize the readers with the concepts of database normalization, concurrency control, deadlock handling and recovery etc., which are extremely vital for a clear understanding of DBMS. To familiarize the readers with the equivalence amongst Relational Algebra, Tuple Relational Calculus, and SQL, a large number of equivalent queries have been provided. The concepts of normalization have been elaborated very systematically by fully covering the underlying concepts of functional dependencies, multi-valued dependencies, join dependencies, loss-less-join decomposition, dependency-preserving decomposition etc. It is hoped that with the help of the information provided in the text, a reader will be able to design a flawless database. Also, the concepts of serializabilty, concurrency control, deadlock handling and log-based recovery have been covered in full detail. An overview has also been provided of the issues related to distributed-databases.
Market_Desc: · Anyone needing a focused introduction to database systems Special Features: · Discusses the key role of data in daily business operations and strategic decisions· Explains how to gather and organize critical business information· Demonstrates the use of accepted data modeling procedures to design a relational database· Explains the concept of data normalization and how to use standard normalization rules· Introduces key elements of the SQL language, covering both accepted standards and vendor-specific implementations· Covers how to use SQL language statements to manage databases and retrieve, modify, and maintain data.· Focuses on critical real-world issues including application integration and securing data against disclosure and loss. About The Book: This book walks you through databases and SQL language database management systems, the software on which they are based, from the ground up. Readers will learn how recognize critical business information, design a database based on this information, and how to retrieve and modify that information in a useful manner. The book includes some of the most recent innovations in SQL database systems.
This book is an outgrowth of research done by Dr. Gamt Dijsterhuis for his doctoral thesis at the University of Leiden. However, there are also contributions by several other authors, as well, including Eeke van der Burg, John Gower, Pieter Punter, Els van den Broek, and Margo Flipsen. This book discusses the use of Multivariate Data Analysis to solve problems in sensory and consumer research. More specifically the focus is on the analysis of the reactions to certain characteristics of food products, which are in the form of scores given to attributes perceived in the food stimuli; the analyses are multivariate; and the senses are mainly the senses of smell and taste. The four main themes covered in the book are: (1) Individual Differences, (2) Measurement Levels; (3) Sensory-Instrumental Relations, and (4) Time-Intensity Data Analysis. The statistical methods discussed include Principle Components Analysis, Generalized Procrustes Analysis, Multidimensional Scaling, Redundancy Analysis, and Canonical Analysis. This book will be a value to all professionals and students working in the sensory studies
Drawing on the authors’ varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to include regression analysis, confirmatory factor analysis, structural equation models, and multilevel models. After emphasizing the summarization of data in the first several chapters, the authors focus on regression analysis. This chapter provides a link between the two halves of the book, signaling the move from descriptive to inferential methods and from interdependence to dependence. The remainder of the text deals with model-based methods that primarily make inferences about processes that generate data. Relying heavily on numerical examples, the authors provide insight into the purpose and working of the methods as well as the interpretation of data. Many of the same examples are used throughout to illustrate connections between the methods. In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research. Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer substantive research questions.