Proceedings

DISCUSSION AND CONCLUSIONS
Data continues to grow, and it seems that is happening somehow out of control. But
all this impressive amount of data (even if we assume that we can access and trust it,
so it’s already structured an d organized in data warehouses or even analytical data
marts, which is usually difficult, time-consuming and expensive) that doesn’t
necessarily mean bigger or deeper insights for business. The only way for that is
through powerful analytics and interactive reporting tools that deliver high
performance results.
Analytical tools enable greater transparency, and can find and analyze past and
present trends, as well as the hidden nature of data. However, past and present insight
and trend information are not enough to be competitive in business. Business
organizations need to know more about the future, and in particular, about future
trends, patterns, and customer behavior in order to understand the market better. To
meet this demand, many BI vendors developed predictive analytics to forecast future
trends in customer behavior, buying patterns, and who is coming into and leaving the
market and why.
As Nigel Rayner noted in his speech at the annual Gartner Business Intelligence
Summit in 2009: “The business intelligence market is a perennial evergreen. While it
has seen ups and downs in the past decade, its growth vector remains strong, and
aggregate revenues should exceed $ 12 billion by 2014. New categories continue to
emerge and be absorbed into core BI. The current crop includes business
performance solutions, text analytics, predictive analytics and data mining and
complex event processing. …By 2012, 33% of analytic applications applied to
business processes will be delivered through course –grained application mashups.”
In our opinion, business analytics, operational business intelligence, the agile
enterprise, the need for powerful insight tools are the most important trends connected
to business intelligence today. It’s future lies in systems that can guide and deliver
increasingly smart decisions in a volatile and uncertain environment. In this context,
it’s extremely important both for business managers and BI professionals to cooperate
in order to implement in organizations the right analytical tools, that respond to each
particular user needs: from ad-hoc report navigation to ad-hoc report creation and
develop of predictive models. An information and intelligence insights partnership
should function between business people of different competencies and roles
regarding business intelligence. And that is where the future research must be focus
on (together with attempts to define a more widely accepted methodology for the
process of predictive modeling itself), as we have the tools for predictive analytics, we
recognize the need and it’s business value but still “we are sitting on a mountain of
gold but we’re not mining it as effectively as we could” (M. Masciandro, director of
BI at Rohm & Haas: 2011).
REFERENCES
Albescu F., Pugna I. and Paraschiv D (2008)., “Business Competitive Intelligence – the
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Azvine B., Cui Z., Majeed B and Spot M (2007) “Operational risk management with real time
business intelligence”. BT Technology Journal vol. 25, nr. 1 :154-167
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