Chapter 5. Business Intelligence 109
5.3.2 Data warehousing: The big picture
To remain competitive, organizations need to improve profitability, reduce costs,
and respond faster to competitors’ moves, market opportunities, regulatory
changes, and day-to-day process exceptions. Such requirements can be directly
influenced by using the data in the data warehouse.
The data warehouse functions go beyond a repository of historical business
information used by for front-line business decision makers for strategic and
tactical analysis and decisions. It also can incorporate current and transactional
data that can be used to improve operational business decisions. The enterprise
is becoming more and more unified and integrated. The layered data architecture
supports this and enables it just like the ongoing integration of BI and the
business processes. An integrated enterprise strategy is key, and the more
robust hardware and software to support it are here today.
Analytic applications are also used more frequently to deliver data and initiate
corrective processes and activities in right time. Activities that require immediate
action for a specific operation of the business might include system-generated
information or guided analysis sourced from a data warehouse. Information from
specific and current transactions could be used to trigger alerts and support
strategic decisions to avoid risk exposure and assure compliance.
Looking at the big picture, as represented by Figure 5-10 on page 110, the data
warehouse can be integrated with an SOA and deliver information to consumers,
such as processes and applications. Here, the different data integration
technologies are applied to assure that the information is timeless and consistent
across the enterprise.
110 Improving Business Performance Insight
Figure 5-10 Right-time enterprise data warehouse
Certain high volume transaction systems require specialized applications to
automate tasks that require operational decisions. For example, an insurance
company could use an Internet application to explore a new and large market of
potential customers. Traditionally, the process of generating an insurance quote
requires an assessment of the potential risk factors for the customers. The
current stage of development of the technology allows an insurance company to
implement a model-based underwriting system and deploy it into a process
server that can provide immediate responses to Web policy applicants. This
process can utilize information from a data mining application, for example, a
score, to perform a risk assessment, and, based on a predefined threshold,
accept or reject the application. Such a process could lead to increased revenue,
cost reduction, and lowered risks.
Similar systems could be applied to automate the operational decision process in
other industries, not only for fully automated activities, but also to improve the
decision making processes of activities that require human intervention. For
example, a Call Center operator could potentially use information from a data
warehouse for promotional offering personalization.
In order to succeed in the integration of operational and strategical systems, you
need to consider the implementation of a enterprise data integration policy. You
Integration
Business
Operation
Information
Consumers
(Processes and
Applications)
Master Data Management
Product
Customer
Applications, Operational Systems
Enterprise Service Bus
Events, Notifications, Triggers (message)
Information Delivery Services
Feeds
Trickle Feed
ETL, EII
Trickle Feed
Enterprise Application Integration
Information
Data
Warehouse
EDW, ODS and Data Marts
HR
Finance
Sales
CRM
Marketing
3
rd
Party
External Data

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