3 It ensures real time reporting, data quality and


Data warehouse
supports an organization to collect analyses and interpret various data for
decision making. It ensures real time reporting, data quality and data availability with reduced latency. The following
section describes the findings from the reviewed literature subjected to effectiveness
in data warehouse implementation. The findings are categorized into organizational and technical
factors as follows;

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3.1 Organizational factors

The organizational factors are considered to be one of
the basic successors of data warehouse implementation; such as management
support and users involvement (Watson and Ariyachandra, 2005). Moreover, researchers conducted an exploratory study and illustrated that organizational factors must be
considered for data warehouse implementation effectiveness (Mannino et al, 2006).

involvement in data warehouse development is most important for successful
implementation (Wixom and Watson, 2001). As a result, users create awareness of
the boundaries and abilities of the data warehouse and contribute to the
further improvement (Kimball et al, 2008). Moreover, involving users is
encouraged to systems that imply change in an organization (Kelly, 2001).

Users are involved by being assigned different roles
and tasks to enhance user requirements collection. This may lead to the
availability of clean data for the efficiency and effectiveness of the data
warehouse, and thus quality reports are generated for credible decision making (Keil & Carmel, 1995). Accordingly, user’s
involvement ensures the valuable and consistent data warehouse (Rahman, 2013;
Rahman, 2014). Thus, user participation in the development of data and access
modeling is a critical success factor in data warehouse development (Sharda et
al, 2014).

weak management support influences failure in data warehouse implementation. This
relies on the management ability of planning and making decisions. If management
plans are systematic, people within the organization will support data
warehouse process (Frolick and Lindsey, 2003). Moreover, managers are required
to provide frequent and organized training on data warehouse to create
understanding on diverse functions of the system (Teo et al, 2000). Therefore,
management support enhances the effectiveness development and implementation of
data warehouse (Ariyachandra et al, 2005).

many organizations lack success in data warehouse implementation owing to
shortage of fund to accomplish the project. For example, fund to facilitate the
frequent trainings to users (Frolick and Lindsey, 2003). Therefore, management
support and a strong project champion can ensure that a data warehouse project
will receive the resources necessary for successful implementation. The next
section describes the technical elements for data warehouse success as follows;

3.2 Technical factors

One of the important parts in data
warehouse development is the design of the data model. Thus, data warehouse
architects and application
developers must understand technical issues, such as the
integration of the entire components needed for the design, transformation,
storage, and management of data warehouse (Yaseen,
2014). Additionally, the team skills needed to develop and implement a data
warehouse includes in-depth knowledge of the database technology and
development tools used which influences loading and maintain a data warehouse (Sharda
et al, 2014).


During data modeling, expertise is required to
determine what data are needed, define business rules associated with the data,
and decide what aggregations and other calculations may be necessary ( Sharda
et al, 2014). However, developers must have the
ability to select appropriate technologies and models that fit the
organizational needs. The following part is the discussion of the findings.


The results section identified significant factors for
effective data warehouse implementation. In this sense, it is evident that most
researchers agreed on the competitive advantage of data warehouse for decision
support, and emphasized organizations to employ all factors for success. However,
Sharda et al. (2014) depicted that, technical issues are important, but often
not as important as behavioral issues, such as meeting upper management’s
information needs and user involvement in the development process. This implies
that, the implementation success is context based. Moreover, for the effective data warehouse implementation both
research and practice are most important aspects to be considered (Hwang and Xu,
2008). Therefore, for an organization to acquire the modest advantage, both organizational and technical factors must be
considered during the implementation to ensure its effectiveness (Chenoweth, Corral,
and Demirkan, 2006). 

of researchers argued on the factors for effectiveness of data warehouse implementation
such as management support, user involvement and technical factors. However, data warehouse development needs
to take into consideration the organization’s vision, structure, and culture
for effectiveness (Matney, 2003). Moreover, the organization is required to
examine data warehouse vendors when the plan and support for a data warehouse are
established. Additionally, data
warehouse should be scalable to extent that, it can maintain its effectiveness
regardless of the unclear organizational politics and turnover of organizational
employees (Frolick and Lindsey, 2003). Furthermore, it is useful choosing a data warehouse manager who is technology
oriented rather than user oriented. Based on the findings, it is shown that data warehouse
development is complicated because it requires many efforts, time and costly. Thus,
many researchers might argue on the factors for considerations to ensure data
warehouse effective implementation.


Data warehouse has developed
as vital part of large business organizations. Ensuring decision making support
to business organizations thus, effective data warehouse have to be developed
and implemented. Building a data warehouse is a complicated process, since it requires
many efforts and several resources. Based on the literature review, organizational and technical factors need to
be considered carefully for successive implementation. Moreover, other researchers
have argued on additional factors for considerations such as the mission,
vision and organizational politics. Additionally, the author has addressed the
difficulties of data warehouse implementation and calls for more in-depth
studies to explore the factors for effective data warehouse implementation.



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