Mining Interesting Aggregate Tuples

In business intelligence, the concept of data cube offers aggregate views over multiple dimensions of business. Computing the data cube is a challenge because of the exponential number of cuboids. This number is not only an important problem of computing, but also of searching for what is interesting or useful in the data cube. This paper presents the concept of interesting aggregate tuple that can be useful for managers to decide on their business. This concept is useful because (i) interesting aggregate tuples are those with important and credible aggregate values, and (ii) the number of interesting aggregate tuples is very small that can be considered by humans. The algorithm for searching for interesting aggregate tuples is implemented and experienced on the real datasets.