This reduced time and increased accuracy allows Michigan First management to have more flexible reports, including on-demand reports that compare different periods they select. This flexibility will give the credit unions management the ability to have a greater understanding of how trends are going within the credit union allowing it to respond more quickly and accurately to changes.

According to CUTEK Senior Programmer, Eric Lizotte, the core goal of the project was make all internalized reporting simpler and more flexible, by moving usable data from SymitarsEpisyssystem into an SQL database. Importantly, the credit union wanted the data to include historical information that was easier to access. The Symitar ODBC extract, which is a good daily snapshot, doesnt provide an easy way to get, for example, total share balances for a specific branch two weeks ago. Other goals of the project were to automate a number of the existing daily and weekly reports, as well as to automate (as much as possible) the collection of data for the NCUA quarterly call report.

We have worked with CUTEK on various projects and have always received top-notch service and response time. With their Symitar expertise, database knowledge and also the comfort level that our staff has working with CUTEK, it was a perfect fit, says Michigan First Programmer, Denny Howell. We will be able to respond to current and developing trends much faster and with more accuracy, using the integration between the data warehouse database and our dashboard product for real-time stats or anomalies.

CUTEK built the database structures, custom import code, SQL jobs, and SQL scripts to automate the process. We also worked with the staff on a number of different reports internally, Lizotte explains. Interestingly, we found a number of data inconsistencies with how things had been reported in the past in the process, as well as a couple of errors in how things were being imported on the host side.

Michigan First requested assistance from CUTEK because structuring fast, effective database structures for historical storage of data requires a fairly deep knowledge of SQL, while at the same time having good knowledge of what sort of data elements credit unions will find most valuable. It definitely has been a collaborative effort, Lizotte adds. The staff at Michigan First did a fair bit of work both with some of the reporting pieces as well as just working with us to figure out just where data points were stored and what the rules for those data points were.

Along with the credit union benefiting from this new data warehouse, its members will benefit by enhanced service from the credit union as well as more accuracy in calculations of things like reward programs.