By now, we’re all getting used to the new (less than ideal) normal in sports — watching our favorite athletes play their games in empty arenas
With so much data in your own stores, it’s tempting to think you have all you need to start producing great predictive insights. This might be
Your machine learning model is only as good as the data you feed into it. That makes data preparation (or cleaning, wrangling, cleansing, pre-processing, or any
Congratulations! You’ve embraced machine learning and data science and your organization is well on its way to building a system that helps you deploy predictive analytics
Pinpointing the most useful machine learning data and figuring out how to combine sources to create accurate, meaningful models is one of the most business-critical areas
The previous decade has been one of impressive growth and massive profits for financial services providers. As the global economy bounced back from the recession, new
“Only a crisis — actual or perceived — produces real change.” – Milton Friedman The start of 2020 has been one of the most turbulent on
There are some insights that can only come from the data you produce or collect in-house. Historical sales figures, for example. Foot traffic through your store.
Data enrichment is a crucial step in the modeling process that data scientists tend to overlook due to the difficulty in finding and utilizing external sources.