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The topic of real-time business intelligence (BI) has had steady interest since
the turn of the century. Back in 2003, The Data Warehouse Institute (TDWI) performed
a study that showed 50 percent of respondents were deploying or planned to deploy
"Real-Time BI" projects. Global 24/7 markets, just-in-time business
processes, adaptive sales and marketing processes, and increased customer service
all contribute to the need for faster decision making and actions.
To date, Complex Event Processing (CEP) software has been considered the domain
of development teams building sophisticated real-time applications such as algorithmic
trading or real-time risk management in financial markets. But a growing number
of savvy customers have applied CEP software for next generation real-time analytic
applications in traditional BI environments that drive situational awareness,
faster decisions and immediate actions.
Second-generation CEP platforms have emerged with features that enable BI and
data management professionals to more easily incorporate event processing into
their analytic application suites. Using CEP, these professionals can incorporate
Continuous Intelligence (TM) in a fast, affordable manner to speed decisions
and actions that respond to market activity and opportunities, raise customer
revenue and lower churn, and increase service assurance.
How do we get faster, actionable analytics?
As many of you know, not all business processes are capable of or even designed
for working in "real-time." But many customer-facing, revenue-related
and operational processes could fully take advantage of just-in-time, situational
intelligence to drive faster actions that enhance customer relationships, maximize
revenue opportunities, and ensure the risk-free delivery of products and services.
Faster, actionable analytics is easier said then done -- at least so far. When
BI and development teams look at such applications, they encounter daunting
challenges:
- Gathering large volumes of constantly changing data from various customer
or operational touch-points
- Integrating this high volume data with existing customer and operational
information to provide full situational context
- Continuously analyzing all this information to identify problems and opportunities
and derive the proper course of action
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