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(Michalewicz et al., 2007). Artificial Intelligence is,
in this manner, incorporated on BI systems.
5 TRENDS AND OPEN ISSUES
It is difficult to be comprehensive on the coverage of
such a vast area hence a choice was made to
highlight the trends and research issues considered
most relevant.
One trend is Pervasive BI , or BI for the masses
(Eckerson, 2008; Lunger, 2008; Negash, 2004).
There is a concern on delivering BI to all levels of
an organization. Another trend is Real-time BI or
Operational BI, which pretends to deliver
information based on real time data, as opposed to
historical data (Brobst & Pareek, 2009; Klawans,
2008; Negash, 2004). Other point concerns on how
to deal with the increasing quantities of data
available for BI systems (Klawans, 2008; Strenger,
2008). Emphasis is also being placed on cultural
aspects and on the human side of BI (Hobek et al.,
2009; Lin et al., 2009; Watson, 2009).
Some research issues that have been identified in
the literature in DSS could also be explored in the BI
area, namely, integration issues, analysis of
usability, assessment, return on investment, and
technological issues. A research area could analyze
and evaluate technologies that are potentially
applicable to analysis and understanding (Nemati et
al., 2002). Powerful analytical tools, such as DM,
remain too complex and sophisticated for the
average consumer, therefore, another area of
research could be the development of more effective
human-computer interfaces (Clark et al., 2007;
March & Hevner, 2007).
6 CONCLUSIONS AND FUTURE
WORK
According to the present analysis, BI is an emergent
dynamic area. The presented framework can be used
as the basis for subsequent research, since it helps to
operationalize the actual state of the art. Research
could be developed along all the presented levels
(Figure 2), since there are open issues on all of them.
The associations with knowledge management,
competitive intelligence, and artificial intelligence,
have a great potential for development, and for
research.
Investigation areas on BI could include
integration issues, analysis of usability, assessment,
return on investment, and technological issues.
As future work the authors will explore the
usage of DM tools on BI, considering the
Knowledge Discovery on Databases (KDD) process,
as presented by (Fayyad et al., 1996). It is their
belief that only the full integration of the KDD
process on BI can conduct to an effective usage of
DM on BI.
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