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Books in Database management

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61-70 of 161 results in All results

Principles of Data Integration

  • 1st Edition
  • June 25, 2012
  • AnHai Doan + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 4 1 6 0 4 4 - 6
  • eBook
    9 7 8 - 0 - 1 2 - 3 9 1 4 7 9 - 8
Principles of Data Integration is the first comprehensive textbook of data integration, covering theoretical principles and implementation issues as well as current challenges raised by the semantic web and cloud computing. The book offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand. Readers will also learn how to build their own algorithms and implement their own data integration application. Written by three of the most respected experts in the field, this book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. This text is an ideal resource for database practitioners in industry, including data warehouse engineers, database system designers, data architects/enterprise architects, database researchers, statisticians, and data analysts; students in data analytics and knowledge discovery; and other data professionals working at the R&D and implementation levels.

Joe Celko's Trees and Hierarchies in SQL for Smarties

  • 2nd Edition
  • January 20, 2012
  • Joe Celko
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 3 8 7 7 3 3 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 3 8 7 7 5 6 - 7
The demand for SQL information and training continues to grow with the need for a database behind every website capable of offering web-based information queries. SQL is the de facto standard for database retrieval, and if you need to access, update, or utilize data in a modern database management system, you will need SQL to do it. The Second Edition of Joe Celko's Trees and Hierarchies in SQL for Smarties covers two new sets of extensions over three entirely new chapters and expounds upon the changes that have occurred in SQL standards since the previous edition's publication. Benefit from mastering the challenging aspects of these database applications in SQL as taught by Joe Celko, one of the most-read SQL authors in the world.

Data Mining: Concepts and Techniques

  • 3rd Edition
  • June 9, 2011
  • Jiawei Han + 2 more
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 3 8 1 4 8 0 - 7
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

Data Architecture

  • 1st Edition
  • March 23, 2011
  • Charles Tupper
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 3 8 5 1 2 6 - 0
Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality. The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management.

Database Modeling and Design

  • 5th Edition
  • February 10, 2011
  • Toby J. Teorey + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 3 8 2 0 2 0 - 4
  • eBook
    9 7 8 - 0 - 1 2 - 3 8 2 0 2 1 - 1
Database Modeling and Design, Fifth Edition, focuses on techniques for database design in relational database systems. This extensively revised fifth edition features clear explanations, lots of terrific examples and an illustrative case, and practical advice, with design rules that are applicable to any SQL-based system. The common examples are based on real-life experiences and have been thoroughly class-tested. This book is immediately useful to anyone tasked with the creation of data models for the integration of large-scale enterprise data. It is ideal for a stand-alone data management course focused on logical database design, or a supplement to an introductory text for introductory database management.

Data Mining

  • 3rd Edition
  • February 3, 2011
  • Ian H. Witten + 2 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 8 9 0 3 6 - 4
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise.

Developing High Quality Data Models

  • 1st Edition
  • December 30, 2010
  • Matthew West
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 3 7 5 1 0 6 - 5
  • eBook
    9 7 8 - 0 - 1 2 - 3 7 5 1 0 7 - 2
Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models. The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool. This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling.

Securing SQL Server

  • 1st Edition
  • December 27, 2010
  • Denny Cherry
  • English
  • eBook
    9 7 8 - 1 - 5 9 7 4 9 - 6 2 6 - 1
Securing SQL Server: Protecting Your Database from Attackers provides readers with the necessary tools and techniques to help maintain the security of databases within their environment. It begins with a discussion of network security issues, including public versus private IP addresses; accessing an SQL server from home; physical security; and testing network security. The remaining chapters cover database encryption; SQL password security; SQL injection attacks; database backup security; security auditing; and server rights. The Appendix features checklists that database administrators can use to pass external audits.

Joe Celko's SQL for Smarties

  • 4th Edition
  • October 18, 2010
  • Joe Celko
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 3 8 2 0 2 3 - 5
Joe Celkos SQL for Smarties: Advanced SQL Programming offers tips and techniques in advanced programming. This book is the fourth edition and it consists of 39 chapters, starting with a comparison between databases and file systems. It covers transactions and currency control, schema level objects, locating data and schema numbers, base tables, and auxiliary tables. Furthermore, procedural, semi-procedural, and declarative programming are explored in this book. The book also presents the different normal forms in database normalization, including the first, second, third, fourth, fifth, elementary key, domain-key, and Boyce-Codd normal forms. It also offers practical hints for normalization and denormalization. The book discusses different data types, such as the numeric, temporal and character data types; the different predicates; and the simple and advanced SELECT statements. In addition, the book presents virtual tables, and it discusses data partitions in queries; grouping operations; simple aggregate functions; and descriptive statistics, matrices and graphs in SQL. The book concludes with a discussion about optimizing SQL. It will be of great value to SQL programmers.

The Practitioner's Guide to Data Quality Improvement

  • 1st Edition
  • October 15, 2010
  • David Loshin
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 3 7 3 7 1 7 - 5
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 2 0 3 4 - 4
The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers.