Available On-Demand - This webinar has been recorded and is now available for download.
Operationalizing analytics—integrating analytics as part of an operational business process—is a real and growing trend. At TDWI, we see increasing interest in operationalizing analytics (including machine learning) to drive value. This presents both an opportunity and a key challenge as cited by respondents to our surveys. Why is operationalizing models so important?
Operationalizing models enables organizations to take action on them, which is where the value of ML lies. However, while organizations put a lot of emphasis, investment, and resources into model development, operationalizing the models is often overlooked, which increases the time needed to put a model into production and can even cause projects to fail.
Operationalizing models is not just a single action performed by a single individual. It typically requires new roles such as DataOps or ModelOps, especially as organizations look to deploy growing volumes of models. Join us for this TDWI webinar to learn more about why this portion of operationalizing analytics is so critical and what steps your organization can take to unlock the value of your analytical models.
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