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2/27/2004
A research institution with 30,000 students, 10,000 employees, a medical center
and 10 schools, Vanderbilt University generates and manages massive amounts
of data. When our data storage needs expanded in the late 1990s at a rate of
1,000 percent annually, the university’s IT team quickly realized it must
take definitive action.
The university was beginning to face the cost containment and technology management issues associated with maintaining several decentralized databases spanning university and medical center operations. While most universities that run teaching hospitals maintain separate IT systems, Vanderbilt found economy and efficiency in sharing systems while functioning as one organization across academic and clinical programs. To maintain our ability to meet the university’s IT needs, improve access, and lower costs, the IT team determined it must consolidate Vanderbilt’s vital data and storage infrastructure.
Integration was also a priority. Our legacy systems were unable to transform and organize data into the business intelligence the university needed. For example, Vanderbilt’s management could not effectively analyze and manage the costs of services provided by the university’s hospital, which accounted for 70 percent of the medical center’s expenses. Without the means to make data available through Web browsers, Vanderbilt's users also lacked easy access to vital information.
Vanderbilt University addressed its data storage, business intelligence, and budget needs with Linux and Oracle technology. The implementation, launched in 2003, consists of a three-node data warehouse built on Oracle Real Application Clusters on Red Hat Linux teamed with Oracle Application Server. We use one three-server cluster for the production data warehouse and a two-node cluster for testing. If any server in a cluster should fail, the remaining servers continue to operate seamlessly, ensuring high availability.
Vanderbilt projects that the implementation will yield a savings of 185 percent during the next five years, taking into account the performance and availability of the new systems, and the efficiency gained in managing a single vendor’s system.
The new data warehouse system will eventually serve nearly all decision support needs for the university and its medical center. Currently, an elaborate labor-tracking application provides labor decision support management. System users can now easily extract and format vital data into reports for informed decision-making. Additional warehouse data includes alumni and fund-raising records, financial information, and academic and student records.
In 2002, the IT team created a five-year cost model and demonstrated, based on a five-year technology history, that trying to limit costs by buying incrementally would cause huge spikes in capital investments every few years. We would also lose productivity in trying to catch up. This reasoning resonated with senior administrators and won support for the project.
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