Data Warehouse (DW) and Online Analytical Processing (OLAP) technologies are the core of current Decision Support Systems. Traditionally, a data warehouse has been a historical (and relatively
static) repository of data collected from a wide variety of heterogeneous data sources by means of Extraction-Transformation-Loading (ETL) processes. The widespread deployment of both DWs and OLAP technologies is due to the intuitive representation of data provided to data analysts or managers in support of management decisions.
Research in data warehousing and OLAP has produced important technologies for the design, management and use of information systems for decision support. Much of the interest and success in this area can be attributed to the need for software and tools to improve data management and analysis given the large amounts of information that are being accumulated in corporate as well as scientific databases.
Nevertheless, even though the high maturity of these technologies, new data needs or applications currently run at companies not only demand more capacity or storing necessities, but also new methods, models, techniques or architectures to satisfy these new needs. Some of the hot topics in data warehouses include distributed data warehouses, web warehouses, data streaming, GIS or biomedical data. Moreover, there are other aspects very developed in other software areas such as security or quality, which still remain totally uncovered by current design methods or technologies for data warehouses.
Like the previous successful DOLAP workshops held in conjunction with CIKM, the eighth edition of the Workshop on Data Warehousing and OLAP (DOLAP 2005) aims to synergistically connect the research community and industry practitioners. It provides an international forum where both researchers and practitioners can share their findings in theoretical foundations, current methodologies, and practical experiences. This year, DOLAP05 will be specially focused on new research directions, and emerging application domains in the areas of data warehousing and OLAP.