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What do i do with my data now? Integrating an AI/ML approach
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About speaker
As a leader in training and product engagement Megan began her career in certification with over a decade of experience in custom training delivery, sales and management in the pharmaceutical and government sectors. Her focus is to create, promote and maintain high stakes certifications within emerging technologies. Outside of work she is mother of two teenagers, an avid reader, runner and would love to have more time to work in her art studio.
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IoT generates a significant amount of data that can drastically impact business operations. Collecting and analyzing the data to inform business decisions changes dramatically with the big data originating from IoT. We will discuss key factors at the initiation of an AI project which will impact success and avoid overspend. We evaluate considerations of data preparation, selection and integration that should not be neglected when initiating an ML approach. We do this by breaking down the value to an organization derived from internal and external data sources. Finally, we illustrate lessons learned via practical use cases and discuss best practices for building technical requirements based on data characteristics, business drivers and functional limitations within an organization.
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