These Models Need Enterprise Data Management!

Jay Hoecker
Muma Case Review  •  Volume 2  •  2017  •  pp. 001-030
After 28 years of public service, the Information Technology Bureau Chief for the Southwest Florida Water Management District (SWFWMD), Dr. Steven Dicks, was still passionate about serving the public. By first focusing on the needs of people in the District, Dr. Dicks was able to objectively observe the many aspects of operations for which he was responsible. His observations led him to believe that the use of technology within his organization wasn’t as effective and efficient as he knew it could be.
The SWFWMD managed the water resources of 16 Florida counties in an area that was close to 10,000 square miles, with 4.7 million inhabitants. To effectively manage water resources, the organization needed to understand current water needs, prepare for future needs, and protect and preserve water resources within its boundaries. A significant part of managing water resources involved the production and utilization of scientific computer models that help track, predict, and control a plethora of water related challenges. At the SWFWMD, individuals used desktop computers to run most of the scientific models. Given the limited computing capacity of the average desktop computer, running a model was beginning to require too much time; and simple interruptions, such as a system reboot, could jeopardize the ability to complete long model runs. Therefore, the resulting data used and produced was often very ineffectively managed.
Dr. Dicks began to wonder about the current system of producing and managing scientific models, and how the systems might be improved. He evaluated options. He thought upgrading individual desktops could help, but only in the short term because as the data sets and demand for processing power continued to grow, the desktop might always be a step behind. Installing powerful servers to house the data sets and run the models would be a significant improvement, but the cost to acquire and maintain the new system might challenge the budget. A cloud-based solution utilizing an “infrastructure as a service” approach, was a third option, but current system infrastructure compatibility, security, and access needed to be carefully evaluated.
Dr. Dicks believed that data management was just as important as the processing power of an upgrade, and that ultimately the technology that allowed for the most effective EDM system needed to be identified and implemented to best serve the needs of the District into the future.
cloud, enterprise data management, models, SWFWMD, water management
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