Step-by-step process to analyze your data from start to finish

Contained inside the massive volumes of data that your credit union is creating on a daily basis is the insight you need to better understand your members. It contains valuable insights about the individuals, including their wants, needs and dreams. Being able to properly analyze your credit union’s data puts you in the best possible position to serve them with personalized services and better experiences. Let’s explore five essential steps to unlock this invaluable insight.

1. Extract

Data extraction is the process of collecting different types of data from a variety of sources. One of the more prominent of these sources will undoubtedly be your core processing platform. But other sources can include the tools being used by your marketing department, software that is utilized by front-end employees, and anything else that contains personal member information in some way.

2. Cleanse

Next, you’ll need to cleanse your data, which means editing, correcting mistakes, and restructuring it in a more useful way. Begin by removing any irrelevant data from what you’ve extracted. Do the same for duplicate data as well. Address any structural errors that you uncover, manually fill in the missing data gaps, and validate everything to make sure you have the most complete and accurate record to work from.


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