Every predictive model, player segmentation tool, or fraud detector in gambling and gaming depends on data. But raw data isn’t ready to use out of the box. If it’s not cleaned, normalized, and checked for bias, even the best algorithms will return flawed results. This post walks through practical steps for managing data sources correctly—especially when handling behavioral… Continue reading Data Sources: Cleaning, Normalizing, and Avoiding Bias