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The IBM Informix® Dynamic Server (IDS) has the tools to build a powerful data warehouse infrastructure platform to lower costs and increase profits by doing more with your existing operational data and infrastructure. The Informix Warehouse Feature simplifies the process for design and deployment of a high performance data warehouse. With a state-of-the-art extract, load, and transform (ELT) tool and an Eclipse-based GUI environment that is easy to use, this comprehensive platform provides the foundation you need to cost effectively build and deploy the data warehousing infrastructure, using the IBM Informix Dynamic Server, and needed to enable the development and use of next-generation analytic solutions . This IBM® Redbooks® publication describes the technical information and demonstrates the functions and capabilities of the Informix Dynamic Server Warehouse Feature. It can help you understand how to develop a data warehousing architecture and infrastructure to meet your particular requirements, with the Informix Dynamic Server. It can also enable you to transform and manage your operational data, and use it to populate your data warehouse. With that new data warehousing environment, you can support the data analysis and decision-making that are required as you monitor and manage your business processes, and help you meet your business performance management goals, objectives, and measurements.
IBM® Informix® Warehouse Accelerator is a state-of-the-art in-memory database that uses affordable innovations in memory and processor technology and trends in novel ways to boost query performance. It is a disruptive technology that changes how organizations provide analytics to its operational and historical data. Informix Warehouse Accelerator uses columnar, in-memory approach to accelerate even the most complex warehouse and operational queries without application changes or tuning. This IBM Redbooks® publication provides a comprehensive look at the technology and architecture behind the system. It contains information about the tools, data synchronization, and query processing capabilities of Informix Warehouse Accelerator, and provides steps to implement data analysis by using Informix Warehouse Accelerator within an organization. This book is intended for IBM Business Partners and clients who are looking for low-cost solutions to boost data warehouse query performance.
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.
InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects.
Computer Systems Performance Evaluation and Prediction bridges the gap from academic to professional analysis of computer performance.This book makes analytic, simulation and instrumentation based modeling and performance evaluation of computer systems components understandable to a wide audience of computer systems designers, developers, administrators, managers and users. The book assumes familiarity with computer systems architecture, computer systems software, computer networks and mathematics including calculus and linear algebra.·Fills the void between engineering practice and the academic domain's treatment of computer systems performance evaluation and assessment·Provides a single source where the professional or student can learn how to perform computer systems engineering tradeoff analysis·Allows managers to realize cost effective yet optimal computer systems tuned to a specific application
Building a Data Warehouse: With Examples in SQL Server describes how to build a data warehouse completely from scratch and shows practical examples on how to do it. Author Vincent Rainardi also describes some practical issues he has experienced that developers are likely to encounter in their first data warehousing project, along with solutions and advice. The relational database management system (RDBMS) used in the examples is SQL Server; the version will not be an issue as long as the user has SQL Server 2005 or later. The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation. What you’ll learn A detailed understanding of what it takes to build a data warehouse The implementation code in SQL Server to build the data warehouse Dimensional modeling, data extraction methods, data warehouse loading, populating dimension and fact tables, data quality, data warehouse architecture, and database design Practical data warehousing applications such as business intelligence reports, analytics applications, and customer relationship management Who this book is for There are three audiences for the book. The first are the people who implement the data warehouse. This could be considered a field guide for them. The second is database users/admins who want to get a good understanding of what it would take to build a data warehouse. Finally, the third audience is managers who must make decisions about aspects of the data warehousing task before them and use the book to learn about these issues.
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Geared toward designers and professionals interested in the conceptual aspects of integrity problems in different paradigms, Database Integrity: Challenges and Solutions successfully addresses these and a variety of other issues.
Covering the functional characteristics of an on demand computing infrastructure, this book describes the IBM software products that can be used to create a computing infrastructure that has these characteristics. Also discussed is how IBM’s on demand strategy can help a business to make more informed purchasing decisions for IBM application software.