Materialised view construction in data warehouse for decision making

A data warehouse contains historical and summarised data that grows, almost, exponentially with time. It provides a uniform platform for posing decision support queries. These queries are usually analytical and complex in nature and, when processed against a large data warehouse, consume a lot of processing time resulting in an increased query response time. This time can be reduced by using materialised views, which pre-compute the most frequently accessed information and stores them in a data warehouse. In this paper, an algorithm to construct materialised views using previously posed, optimal, user queries on the data warehouse, is proposed. This algorithm defines a heuristic that maximally merges the optimal queries to construct a single materialised view. These materialised views are capable of providing meaningful information for a given future query. Further, experiments are performed to evaluate the effectiveness of the materialised views with respect to the query response time. The experimental results show that materialised views so constructed are capable of answering future user queries in a reduced response time. This would enable effective and efficient decision-making.