Customer data science company dunnhumby is preparing to launch an Enterprise Edition of dunnhumby Model Lab, a machine learning automation tool for data scientists built on Microsoft Azure.
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“Using Azure enabled us to deliver a robust product into end-users’ hands quickly and without the need of a dedicated DevOps team. At launch, we focused on providing free trials, supporting individual users and small data science teams, before expanding to enable larger groups to use the tool.”
As retailers and CPGs begin to reimagine their business operations, and invest in their own data science capabilities, the ability to leverage dunnhumby machine learning expertise is growing. Model Lab enables data scientists to test hundreds or thousands of machine learning models in parallel, freeing their time to focus on delivering value and solving complex retail challenges.
“For several years, Model Lab has been a key tool used by our data scientists, supporting us to deliver customer-first, insight-led solutions,” said Kyle Fugere, Head of Innovation and Ventures at dunnhumby. “Making Model Lab available on Microsoft Azure was a key first step to expanding its audience to end-users, extending the great value this offering brings.”
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Fugere continued, “Using Azure enabled us to deliver a robust product into end-users’ hands quickly and without the need of a dedicated DevOps team. At launch, we focused on providing free trials, supporting individual users and small data science teams, before expanding to enable larger groups to use the tool.”
Victor Robin, data science director at dunnhumby, explains why now is the right time to develop an Enterprise Edition: “Since launch, demand has grown quickly with numerous requests to expand the user limit and dataset size. In response we are developing an Enterprise Edition, which will be available in March 2021. This will support an unlimited number of users and means we can meet the needs of the largest data science teams. Microsoft Azure has been key in enabling us to scale and develop this quickly and securely.”
