The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses

Data warehousing and On-Line Analytical Processing (OLAP) are two of the most signiicant new technologies in the business data processing arena. A data warehouse can be deened as a \very large" repository of historical data pertaining to an organization. OLAP refers to the technique of performing complex analysis over the information stored in a data warehouse. The complexity of queries required to support OLAP applications makes it diicult to implement using standard relational database technology. Moreover, there is currently no standard conceptual model for OLAP. There is clearly a need for such a model and an algebra as evidenced by the numerous SQL extensions ooered by many vendors of OLAP products. In this paper we address this issue by proposing a model of a data cube and an algebra to support OLAP operations on this cube. The model we present is simple and intuitive, and the algebra provides a means to concisely express complex OLAP queries. research interests lie in studying technologies that have the potential to signiicantly impact the automated processing of organizational information. Examples of such technologies include Data Warehousing/OLAP and Workkow Systems. He has published more than 15 papers in refereed journals such as ACM Transactions on Database Systems, IEEE Transactions on Knowledge and Data Engineering, INFORMS Journal of Computing, Information Systems and IEEE Transactions on Systems, Man and Cybernetics. He has also published over 35 conference papers and has chaired as well as served on the program committees of reputed international conferences and workshops. Helen Thomas is a doctoral student in the DuPree College of Management at the Georgia Institute of Technology. Helen was previously a doctoral student in the Management and Information Systems program at the University of Arizona. She has an MSE in Operations Research and Industrial Engineering from the University of Texas at Austin and a BS in Decision and Information Sciences from the University of Maryland at College Park. In addition, she has more than ve years experience in the software consulting industry. Her primary research interests are in decision support databases, which includes eecient OLAP query processing and data modeling for data warehouses/multidimensional databases.