Last Wednesday, Open Data Group had the opportunity to co-host a data science meet-up with DataScope, which manages the Data Science Chicago Meet-Up. We thoroughly enjoyed the experience and appreciate all the folks who came out for discussion and pizza. Bob Grossman, Open Data’s founder and Chief Data Scientist, introduced the concept of AnalyticOps (read CTO Stu Bailey’s posts on the same topic here) and the emerging core competency of deploying models. Bob was joined by Robert Nendorf from Allstate, who shared his views on a similar topic: DevOps for Data Science.
AnalyticOps is an organizational function that fills the gap often found between modelers and developers. Often times, these two functions use different specialized languages and services that lead to significant efforts and delays when moving models from the modeling environment to the deployment environment. AnalyticOps acts as a catalyst to deploy and then monitor and update models.
At the heart of AnalyticOps is an Analytic Engine. An Analytic Engine is a component that is integrated once into products or enterprise IT and then runs new and updated analytic models that are deployed to it in an operational workflows. Although integrated into systems only once, they allow applications to quickly update models as fast as it can read a model file.
Ultimately, AnalyticOps is implemented within an organization to create and maintain a culture where building, validating, deploying, and running analytic models happen in a rapid, repeatable, and reliable system.
To learn more about AnalyticOps and how it assists the growing role of deploying models within a business, feel free to look through Bob’s slide deck from the night. Of course, if you have any questions contact us and we’d be more than happy to discuss the topic with you. Contact us at email@example.com.
Find Bob Grossman’s slides here.