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Model Maintenance: Hidden Costs of Data Science
August 4 @ 11:30 AM - 1:00 PM
Data Analytics is considered the fourth phase of industrialization. Not surprisingly, organizations are rushing to build up and accelerate their data science capabilities. While robustness of data, and availability of talent remain their primary concerns, one of the hidden failure modes is model maintenance. MIT Sloan Tech Review estimates that these costs can add up to several times the cost of model development over the lifecycle of the model. Yet the majority of companies continue to underestimate both the costs and complexity associated with model maintenance. This results in poor ROI, but more importantly, model maintenance is a weight around the ankles of data science teams that results in reduced productivity and attrition.