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<title>LLSC Documents and Publications</title>
<link href="https://hdl.handle.net/1721.1/152929" rel="alternate"/>
<subtitle>Documents and Publications written by the LLSC team</subtitle>
<id>https://hdl.handle.net/1721.1/152929</id>
<updated>2026-04-12T07:43:23Z</updated>
<dc:date>2026-04-12T07:43:23Z</dc:date>
<entry>
<title>Simple Data Architecture Best Practices for AI Readiness</title>
<link href="https://hdl.handle.net/1721.1/152932" rel="alternate"/>
<author>
<name>Gadepally, Vijay</name>
</author>
<author>
<name>Kepner, Jeremy</name>
</author>
<id>https://hdl.handle.net/1721.1/152932</id>
<updated>2023-11-10T03:54:30Z</updated>
<published>2023-11-09T00:00:00Z</published>
<summary type="text">Simple Data Architecture Best Practices for AI Readiness
Gadepally, Vijay; Kepner, Jeremy
AI1 requires data. A core requirement for AI techniques to be successful is high quality data. Hence,&#13;
preparing systems to be “AI Ready” involves collecting raw data and parsing it. There are&#13;
simple techniques that can be applied during initial parsing of raw data that can dramatically reduce&#13;
the effort of applying AI. This document provides a short list of a few best practices for preparing the data.
</summary>
<dc:date>2023-11-09T00:00:00Z</dc:date>
</entry>
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