Simple Data Architecture Best Practices for AI Readiness

dc.contributor.author	Gadepally, Vijay
dc.contributor.author	Kepner, Jeremy
dc.date.accessioned	2023-11-09T20:24:32Z
dc.date.available	2023-11-09T20:24:32Z
dc.date.issued	2023-11-09
dc.identifier.uri	https://hdl.handle.net/1721.1/152932
dc.description.abstract	AI1 requires data. A core requirement for AI techniques to be successful is high quality data. Hence, preparing systems to be “AI Ready” involves collecting raw data and parsing it. There are simple techniques that can be applied during initial parsing of raw data that can dramatically reduce the effort of applying AI. This document provides a short list of a few best practices for preparing the data.	en_US
dc.language.iso	en_US	en_US
dc.rights	Attribution-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nd/3.0/us/	*
dc.subject	Artificial Intelligence	en_US
dc.subject	Data Architecture	en_US
dc.subject	Best Practices	en_US
dc.title	Simple Data Architecture Best Practices for AI Readiness	en_US
dc.type	Working Paper	en_US

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