Utility computing involves pooling computing resources and letting many different tasks draw on them. The goal is to reduce management costs while extracting more use out of existing computing gear and building a system that can adapt quickly to changing business needs. However, the task is complex, requiring sophisticated management software to control and monitor multiple jobs running on a fast-changing infrastructure.
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Business Intelligence
(BI) has made that goal achievable. It can empower
organizations to make their corporate data available
to an unlimited number of people inside and
outside the enterprise, so they can use it to
make faster and more informed decisions, quickly
identify new opportunities, and understand how
well they're performing. But enterprise business
intelligence requires a powerful and flexible
data architecture that will enable an organization
to make all its data, regardless of its source
or location, available to an increasing number
of information consumers. An effective data
architecture strategy will satisfy a wide array
of reporting and analysis needs by supporting
a variety of applications and latency requirements.
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It will also minimize expenditures and promote rapid
return on investment by leveraging and extending the
value of existing data warehouses and operational
systems.
For example semiconductor manufacturers
face a never-ending battle to reduce cost, improve
efficiency and enhance customer satisfaction. The
semiconductor industry's unmatched rate of innovation,
however, emphasizes these pressures. Your shareholders
expect companies to grow and be profitable, as product
lifecycles continue to get shorter and customer expectations
higher.
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Business Utility
