Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
OLAP and statistical databases: similarities and differences
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Database abstractions: aggregation and generalization
ACM Transactions on Database Systems (TODS)
A survey of logical models for OLAP databases
ACM SIGMOD Record
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Building a real Data warehouse for Market Research
DEXA '97 Proceedings of the 8th International Workshop on Database and Expert Systems Applications
MIRABEL DW: managing complex energy data in a smart grid
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
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Schema design is one of the fundamentals in database theory and practice as well. In this paper, we discuss the problem of locally valid dimensional attributes in a classification hierarchy of a typical OLAP scenario. In a first step, we show that the traditional star and snowflake schema approach is not feasible in this very natural case of a hierarchy. Therefore, we sketch two alternative modeling approaches resulting in practical solutions and a seamless extension of the traditional star and snowflake schema approach: In a pure relational approach, we replace each dimension table of a star / snowflake schema by a set of views directly reflecting the classification hierarchy. The second approach takes advantage of the object-relational extensions. Using object-relational techniques in the context for the relational representation of a multidimensional OLAP scenario is a novel approach and promises a clean and smooth schema design.