But First, is the Data Any Good?
Garbage in, garbage out. Anyone who works with data is familiar with this phrase. If you start with messy, inconsistent data, you will generate inaccurate analyses. I recently had 2 different conversations with people about the quality of their data. They were looking to implement a predictive analytics solution but they know that before they can even begin, they need to audit their data for quality. This made me think of how Jordan Story, a Marketing Analyst at St. Leo University had approached this problem at her institution with the use of Rapid Insight Veera Construct.
“As I was playing with the data I realized that we had a lot of inconsistencies between our systems which could have a huge impact on our reporting, the conclusions that we start making and at the end of the year in the analysis we were doing, and a lot of the decisions that we were making were all based on this data.” – Jordan Story
We did an interview with Jordan where she shared her approach and strategy. I thought it was worth resharing.