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How Existing Businesses Should Organize Their Data Assets for AI

How Existing Businesses Should Organize Their Data Assets for AI

FromThe AI in Business Podcast


How Existing Businesses Should Organize Their Data Assets for AI

FromThe AI in Business Podcast

ratings:
Length:
30 minutes
Released:
Jul 22, 2018
Format:
Podcast episode

Description

Companies with wells of data at their disposal may find themselves asking how they can use them in meaningful ways. Generally speaking, a clean set of data is the foundation for AI applications, but business owners may not know how exactly to organize their data in a way that allows them to best leverage AI. How exactly does a business transition from having data with the potential for usefulness to having data that’s going to allow for an accurate, helpful machine learning tool—one that can actually help solve business problems? In this episode of the podcast, we speak with Bryon Jacob, Co-founder and Chief Technology Officer at data.world, a company that offers products and services that help enterprises manage their data. In our conversation, Bryon walks us through the common errors companies make when creating and organizing data sets, and how these companies can transition to a more organized and meaningful data management system. The details in this interview should provide business leaders with a better understanding of some of the processes involved in getting started with AI initiatives, and how to hire data science-related roles into a company. See the full interview article with Bryon Jacob live at:  https://www.techemergence.com/how-existing-bus…ta-assets-for-ai/
Released:
Jul 22, 2018
Format:
Podcast episode

Titles in the series (100)

Learn what's possible - and what's working - with artificial intelligence in the enterprise. Each week, Emerj founder Daniel Faggella interviews top AI and machine learning-focused executives and researchers in sectors like Pharma, Banking, Retail, Defense, and more. Discover trends, learn about what's working now, and learn how to adapt and thrive in an era of AI disruption. Be sure to subscribe to "AI in Industry."