How One CU Is Providing Management With Data More Quickly

Register now

Credit union managers want data-data for daily operations and data for strategic planning. At one credit union here, the IT manager here provides it quickly with Structured Query Language- (SQL) based tools.

"Even when we get in a new product, we can immediately access data with SQL," said Tim Doran, systems manager at Mon-Oc FCU. "We don't have to worry about buying unwieldy custom interfaces to extract data for each vendor. And we save on time and programming costs in designing our own export interfaces."

The $115-million CU is considering a new automobile title-tracking system, for example, but only after ensuring that the system had SQL access. The DataSafe-SQL data mining solution, provided by Valley Forge, Penn.-based USERS, Inc., is used by 55 CUs as an alternative to time-intensive standard reports for data analysis.

DataSafe-SQL is based in the open architecture of a cache post- relational database, which also fuels USERS' transaction processing offering, DataSafe.

SQL-extracted data has empowered about 20 employees across every department since the credit union starting using it three years ago, Doran said.

"I couldn't even tell you where the benefit of SQL begins and ends. Something like 80% of our data now comes through SQL."

For its courtesy pay program, Mon-Oc, serving 35,000 members of Monmouth and Ocean Counties, also uses SQL data to automatically identify when members cross the line.

The systems department exports checking account data into Microsoft Excel reports, making it easy for non-technical staff to see which members' accounts have been overdrawn for five, 15, or 30 days. "Without SQL, generating these reports would be a much, much harder manual process," Doran added.

The same data then feeds into overdrawn notices, which are sent to members in Microsoft Word format.

Mon-Oc employees are able to work with fresh data, as a real-time query can be run in an average of five to 30 seconds, Doran said ven searches on large amounts of historical data only take a few hours.

Doran's caveat: "Make sure your system has resources to handle live queries. Sometimes major, number-crunching queries can slow down an entire CPU."

Before SQL, Doran's only choice for fulfilling staff requests for data was a standard report writers program. Setting up, scheduling, running, monitoring, and distributing the reports took so much time that sometimes requests couldn't be met.

Mon-Oc hasn't rid itself of report writers, however: Report writers are better suited to large data extracts than SQL.

"It's easier to schedule simple outputs of data from large extracts of data in Report Writer that would take a long time to run with SQL," said Doran.

For reprint and licensing requests for this article, click here.