Effective Historization System From Arbitrary Object Linking And Embedding For Process Control United Architecture Servers

Effective Historization System from Arbitrary Object Linking and Embedding for Process Control United Architecture Servers

Smarter Modeling of IBM InfoSphere Master Data Management Solutions

This IBM® Redbooks® publication presents a development approach for master data management projects, and in particular, those projects based on IBM InfoSphere® MDM Server. The target audience for this book includes Enterprise Architects, Information, Integration and Solution Architects and Designers, Developers, and Product Managers. Master data management combines a set of processes and tools that defines and manages the non-transactional data entities of an organization. Master data management can provide processes for collecting, consolidating, persisting, and distributing this data throughout an organization. IBM InfoSphere Master Data Management Server creates trusted views of master data that can improve applications and business processes. You can use it to gain control over business information by managing and maintaining a complete and accurate view of master data. You also can use InfoSphere MDM Server to extract maximum value from master data by centralizing multiple data domains. InfoSphere MDM Server provides a comprehensive set of prebuilt business services that support a full range of master data management functionality.

Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery technology is emerging as a key technology for enterprises that wish to improve their data analysis, decision support activities, and the automatic extraction of knowledge from data. The objective of the Third International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2001) was to bring together researchers and practitioners to discuss research issues and experience in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. The conference focused on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covered the most recent and relevant topics in the areas of association rules, mining temporal patterns, data mining techniques, collaborative filtering, Web mining, visualization, matchmaking, evelopment and maintenance of data warehouses, OLAP, and distributed data warehouses. These proceedings contain the technical papers selected for presentation at the conference. We received more than 90 papers from over 20 countries, and the program committee finally selected 34 papers. The conference program included one invited talk: “Knowledge Management in Heterogeneous Data Warehouse Environments” by Professor Larry Kerschberg, George Mason University, USA.