Given the rapid growth of data it is important to extract mine and discover useful information from databases and data ware houses The process of data cleansing is crucial because of the garbage in garbage out principle Dirty data les are prevalent because of incorrect or missing data values inconsistent value naming conventions and incomplete information Hence we may have multiple records refe...

A data warehouse stores materialized views over data from one or more sources in order to provide fast access to the integrated data, regardless of the availability of the data sources. Warehouse views need to be maintained in response to changes to the base data in the sources. Except for very simple views, maintaining a warehouse view requires access to data that is not available in the view ...

Database community has made significant research efforts to optimize query processing on GPUs in the past few years. However, we can hardly find that GPUs have been truly adopted in major warehousing production systems. Preparing to merge GPUs to the warehousing systems, we have identified and addressed several critical issues in a threedimensional study of warehousing queries on GPUs by varyin...

Technological advances in sensing technologies and wireless telecommunication devices enable novel research fields related to the management of trajectory data. As it usually happens in the data management world, the challenge after storing the data is the implementation of appropriate analytics for extracting useful knowledge. However, traditional data warehousing systems and techniques were n...

The data warehousing and OLAP technologies are now moving onto handling complex data that mostly originate from the Web. However, intagrating such data into a decision-support process requires their representation under a form processable by OLAP and/or data mining techniques. We present in this paper a complex data warehousing methodology that exploits XML as a pivot language. Our approach inc...

Data warehousing has been touted to be the "solveall" for the decision making managers. This is an exaggeration, as the problem of lack of data quality in data is one of the fundamental obstacles in the current data warehousing environment. The erroneous data can significantly affect an organisation, not to mention the frustration of the users of the data warehouse. In this paper, the researche...

This talk will present emerging data warehousing reference architectures, and focus on trends and directions that are shaping these enterprise installations. Implications will be highlighted, including both of new and old technology. Stack seamless integration is also pivotal to success, which also has significant implications on things such as Metadata. Trends in Data Warehousing Industries ex...

Data warehouse [2,4,5,6] is an integrated repository derived from multiple source (operational and legacy) databases. The data warehouse is created by either replicating the different source data or transforming them to new representation. This process involves reading, cleaning, aggregating and storing the data in the warehouse model. The software tools are used to access the warehouse for str...