The value of data science teams’ work isn’t fully realized until the models they’ve built are operationalized so they can actually impact the business. And once they’re in production, it’s critical to monitor their performance so you can trust the predictions they’re making. In many organizations, this responsibility falls to either the IT team, who has insufficient tools to assess model performance, or the data science team, taking time away from important, value-added projects they’d rather be working on.
Watch this webinar, hosted by Domino’s Samit Thange and Bob Laurent, to learn more about the factors that can cause model performance to decrease, as well as some of the leading indicators to predict when it’s time to re-train or re-build a model. You’ll also learn about European insurer Topdanmark and their first-hand experience with an exciting new product from Domino that’s changing their approach to model monitoring.
Domino Model Monitor (DMM) offers complete insight and visibility into the health of all production models across multiple platforms. Gone are the days of worrying about production models left untracked; DMM prevents the financial loss and deprecated customer experience that can occur when production models aren’t properly looked after, creating a “single pane of glass” to monitor the performance of all models across your entire organization.