Abstract: A data warehouse as a storehouse is a repository of data collected from multiple data sources (often heterogeneous) and is intended to be used as a whole under the same unified schema. A data warehouse gives the option to analyze data from different sources under the same roof. If the executive of the company wants to access the data from all stores for strategic decision-making, future direction, marketing, etc., it would be more appropriate to store all the data in one site with a homogeneous structure that allows interactive analysis. In other words, data from the different stores would be loaded, cleaned, transformed and integrated together. To facilitate decision-making and multi-dimensional views, data warehouses are usually modeled by a multi-dimensional data structure. In this paper, we present a framework for selecting best materialized view so as to achieve the effective combination of good query response time, low query processing cost and low view maintenance cost in a specified storage space constraint. The framework implementation parameter includes query frequency cost, query storage cost and query processing cost. The framework select the best cost effective materialize views to optimize the query processing time thereby resulting efficient data warehousing system.
Keywords: Data Warehouse Materialization, View-Maintenance, Access Frequency, Threshold, Query processing cost.
Title: An Approach for Efficient Query Processing For M.V. Selection and Maintenance
Author: Sapna Kose, Swati Shirbhate, Prof. Pravin O. Balbudhe
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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