Introduction Data warehousing has become an increasingly important technology in many organizations, integrating disparate sources of data for decision-making, planning, and policy formulation. Data warehousing applications can be sources of competitive advantage. Even if the raw data is widely available, the strategies for integrating, analyzing, and acting on the information can be differenti...

Data integration is a central problem in the design of Data Wareshouses and Decision Support Systems. When data passes from the sources of the application-oriented operational environment to the Data Warehouse, possible inconsistencies and redundancies should be resolved, so that the warehouse is able to provide an integrated and reconciled view of data of the organization. Generally speaking, ...

The theory of rough sets [15,16], based on the universal framework of information systems, provides a powerful model for representing patterns and dependencies both in databases and in data mining. On the one hand, although there are numerous rough set applications to data mining and knowledge discovery [10,18], the usage of rough sets inside the database engines is still quite an uncharted ter...

Due to the complexity of real-world applications, the number of databases and the volume of data have increased tremendously. Discovering qualitative and quantitative patterns from databases in such a distributed information-providingenvironment has been recognized as a challenging task. In response to such a demand, data mining and data warehousing techniques are emerging to extract the previo...

was largely unknown. Today, many companies are receiving considerable business value from their warehousing efforts, as seen in the following examples: ❑ First American Corporation (FAC), a regional bank located in the Southeast, lost $60 million in 1990 and was operating under letters of agreement with regulators. A new senior management team developed a customer intimacy strategy with a data ...

During the past decade, data warehousing has been widely adopted in the business community. It provides multi-dimensional analyses on cumulated historical business data for helping contemporary administrative decision-makings. Nevertheless, it is believed there is only about 20% information can be extracted from data warehouses concerning numeric data only, the other 80% information is hidden i...

Data warehousing solutions work as information base for large organizations to support their decision making tasks. With the proven need of such solutions in current times, it is crucial to effectively design, implement and utilize these solutions. Data warehouse (DW) implementation has been a challenge for the organizations and the success rate of its implementation has been very low. To addre...

─ Information hidden or stored in unstructured data can play a critical role in making decisions, understanding and conducting other business functions. Integrating data stored in both structured and unstructured formats can add significant value to an organization. With the extent of development happening in Text Mining and technologies to deal with unstructured and semi structured data like X...

IntroductIon With the phenomenal growth of electronic data and information, there are many demands for developments of efficient and effective systems (tools) to address the issue of performing data mining tasks on data warehouses or multidimensional databases. Association rules describe associations between itemsets (i.e., sets of data items) (or granules). Association mining (or called associ...

DATA WAREHOUSING and Online Analytical Processing (OLAP) are essential elements of decision support, which has increasingly become a focus of the database industry. Data Warehouse provides an effective way for the analysis and statistic to the mass data and helps to do the decision making. Many commercial products and services are now available and all of the principal database management syste...