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OLAP is defined as online analytical processing system to answer the multidimensional queries (Dehne et al., 2008; Lawrence & Rau-Chaplin, 2008; Ravat et al., 2008). Multidimensional queries are complex and operate on huge amount of data, furthermore; these queries are used to managerial decisions in decision support systems (DSS) and data mining.
Multidimensional structures are used to decrease query response time. Multidimensional structures, data cube, are the structures of the Data warehouses to represent data sources.
To achieve analytical process of queries, data cubes store data in different summarization degree related to the aggregation function type. When we have multidimensional data, we can construct a lattice of cuboids which contains data in different level of summarization. The cuboid which stores data in the minimum level of summarization is called “base cuboid” and another cuboid which stores data in the maximum level of summarization is called “apex cuboid”.
Data cubes are pre-computed and stored in data warehouses in the form of materialized views to improve query response time. Data cube computation is time and money consuming and various researches have been done to improve query response time based on parallel processing, index selection and view selection (Agrawal, Chaudhuri, & Narasayya, 2000, Agrawal, Chaudhuri, Kollar, Marathe, Narasayya, & Syamala, 2004; Agrawal, Narasayya, & Yang, 2004; Asgharzadeh Talebi et al., 2008; Chaudhuri, 1997; Le et al., 2007; Taniar et al., 2008; Taniar & Wenny Rahayu, 2002a, 2002b, 2002c, 2002d, 2004).
We focus on view selection techniques which are the main issue to construct data warehouses (Ahmed et al., 2007; Aouiche et al., 2006; Aouiche & Darmont, 2009; Choi et al., 2003; Gong & Zhao, 2008; Gupta, 1997; Gupta & Mumick, 2005; Harinarayan et al., 1996; Hung et al., 2007; Kalnis et al., 2002; Kotidis & Roussopoulos, 1999, 2001; Lawrence & Rau-Chaplin, 2008; Mahboudi et al., 2006; Nadeau & Teorey, 2002; Phan & Li, 2008; Ramachandran et al., 2005; Shah et al., 2006; Shukla et al., 1998; Valluri et al., 2002; Xu et al., 2007; Zhang et al., 2003).
Other important issues in data warehousing are: multidimensional design methodologies, partitioning methods, refreshment mechanisms, building XML data warehouses, and warehousing XML documents (Bellatreche et al., 2009; Chen et al., 2010; Maurer et al. 2009; Romero & Abello, 2009; Rusu et al., 2005, 2006, 2009).
Three choices for view materialization are reported (Han & Kamber, 2006):