Big Data vs. Little Data: Part 1 – Structured and unstructured data

It’s clear now: Data can be one of a company’s most valuable assets if properly stored, managed and analyzed.  What’s unclear to many however, is what data is the most valuable and how to harness the value of each type of data.  There are two main types of data: “Big Data” and “Little Data” or, respectively, unstructured data and structured data. Both types of data can deliver a significant amount of value to a credit union. However, figuring out how to harness each type of data can be a challenge when dealing with the array of different data sources. Finding a healthy balance is key to delivering value without succumbing to analysis paralysis.

Little Data: Structured Data

Little Data, typically, is found within a credit unions operational systems.  Systems that are highly structured and require proper inputs to make them function properly.  These types of systems include, but are not limited to, Loan Origination Systems, Core Systems, Credit Card Processing Systems, etc.  These systems collect member and account information in a conformed fashion and, even more importantly, the transactions that are generated. These transactions represent the behavior of a member. It is fairly easy, with the right tools, to find specific member and the account-related (transactions) information that member has done with the credit union in a structured data source and thereby track behavior.

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