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University of California System Consolidates Job Scheduling Functions with BMC Software

November 28, 2012

BMC Software’s (News - Alert) BMC Control-M Workload Automation job scheduling software is meant to help the various campuses and centers of the University of California System (UC System) consolidate job scheduling functions over a single solution.

Dax Johnson, lead technical architect at the University of California, Berkeley commented, “We had half a dozen or more identified scheduling packages. The biggest challenge for us was to get that into a single view so we could understand how the business was being impacted – how to optimize and make better decisions. Control-M was the tool of choice. It’s going to improve the stability of the production control environment and enable better service level attainment due to jobs completing quicker or within their service level time.”

BMC Software’s BMC Control-M Workload Automation job scheduling system is equipped with more power which helps users replace their older multiple schedulers with one integrated solution. The latest version of the software features a new interface that makes it easier to manage complex, time-sensitive projects and enables workload automation to be easier and more efficient than ever before.

In order to realize its goal for a ‘Center of Excellence for Production Control’, the UC System sought an integrated scheduling solution capable of catering to the requirements of multiple campuses and centers, providing a single viewpoint of operations as well as removing the complexities involved in using multiple tools to schedule batch processing jobs.

BMC’s solution reportedly helped the UC System accomplish these goals and met the needs of disparate internal clients.

Notable features and benefits of BMC Control-M are: streamlines the most common functions required to manage jobs by combining all required activities into a single tool; enables constituents in workload automation to collaborate through a virtual workspace; increases the throughput of the scheduling engine; maximizes system responsiveness and job analysis accuracy; and more. 

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Edited by Braden Becker

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