Cooperative Analytics: The standard data model
by: Nate Wentzlaff
The credit union industry is ripe for a Big Data/Analytics harvest. All the member data is ready; it just needs effective analytics strategies to cultivate its value. In a previous blog, I discussed how credit unions must establish standard internal data sets. This is the foundation for excellence in analytics. As credit unions begin establishing their standard data sets, they must then extend these standards across the industry. Sharing best practices in data set design, and the analytics applications developed on top of them, will level the playing field when credit unions compete with big banks
Cooperative Data
Cooperation is a defining value of credit unions. Sharing best practices among the credit union industry is vital for the future of cooperative finance. One way this can be advanced is through data. Data is the raw material of information. As an industry, credit unions must rally around the data they are collectively gathering. Data is becoming the gold of the information economy and “whoever owns the gold makes the rules.” Credit unions must own their data (gold) and share best practices (rules) around how to most effectively store and share their data within the industry.
Industry Standard Analytic Data Model (ADM)
In order to develop a system to effectively share credit union data for cooperative analytics, there must be a common analytic data model (ADM). Since most credit unions rely on the underlying data structures found in their core and ancillary systems, there can be confusion between systems developed by various vendors. This confusion is multiplied across credit unions attempting to cooperate as an industry. In order to cooperate on analytics, a standard data model must be contrived. CUFX has been developing a system integration platform for the credit union industry, and a large group of credit unions have signed up to support these data standards. A standard ADM will allow credit unions to effectively compete with big banks that have large budgets dedicated to their proprietary analytics programs.
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