Social networks and discovery in the enterprise (SaND)
Inbal Ronen, Elad Shahar, et al.
SIGIR 2009
Enterprises have been storing multidimensional data, using a star or snowflake schema, in relational databases for many years. Over time, relational database vendors have added optimizations that enhance query performance on these schemas. During the 1990s many special-purpose databases were developed that could handle added calculational complexity and that generally performed better than relational engines. DB2® has added a number of features that make it more competitive with these special-purpose databases. In this paper, we define meta-data extensions that allow designers of multidimensional schemas to describe the structure of those schemas to multidimensional query and analysis tools. The SQL (Structured Query Language) extensions include a "cube" object that returns row sets that are "slices" of the cube. We also describe Web services for OLAP (online analytical processing) that provide meta-data for multidimensional data, as well as XML (Extensible Markup Language) query results.
Inbal Ronen, Elad Shahar, et al.
SIGIR 2009
Rolf Clauberg
IBM J. Res. Dev
A. Gupta, R. Gross, et al.
SPIE Advances in Semiconductors and Superconductors 1990
Fan Zhang, Junwei Cao, et al.
IEEE TETC