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DTSTAMP:20260608T115913Z
DESCRIPTION:Click for Latest Location Information: http://dgiq-edw2026.data
 versity.net/sessionPop.cfm?confid=165&proposalid=16478\nData literacy isn&r
 squo;t just a skill&mdash;it&rsquo;s a culture, and it&rsquo;s the foundati
 on of becoming truly AI-ready. This case study takes attendees behind the s
 cenes of Vanderbilt University&rsquo;s journey to build a data- and AI-lite
 rate environment. Rather than sending everyone to a formal class, Vanderbil
 t focuses on building shared understanding: where data comes from, what it 
 means, how it should be used, and how to question both data and AI outputs 
 thoughtfully. The university&rsquo;s approach blends business literacy, str
 ong governance, analytical skills, technical know-how, and clear communicat
 ion into a unified readiness framework. Attendees will see how governance b
 uilds trust, business expertise shapes context, and analytical insights tra
 nslate into compelling stories and responsible AI use. Practical examples h
 ighlight initiatives like data domains, stewardship communities, collaborat
 ive learning, and informal knowledge-sharing networks. Participants will le
 ave with actionable strategies to cultivate a culture where people confiden
 tly explore, interpret, apply, and communicate data&mdash;turning insights 
 into impact and ensuring their organizations are genuinely AI-ready.\n\n
 Data literacy at Vanderbilt combines business literacy, governance, analyti
 cal skills, technical skills, and communication into one integrated framewo
 rk.\n	&nbsp;\n
 Creating a data-literate environment does not mean sending everyone to a fo
 rmal training class; it requires embedding learning, resources, and collabo
 ration into daily work.\n	&nbsp;\n
 Trustworthy data&mdash;and trustworthy AI&mdash;start with strong governanc
 e: accuracy, lineage, context, quality, and responsible use.\n	&nbsp;\n
 Business expertise remains essential for interpreting data, validating AI-g
 enerated outputs, and avoiding flawed or incomplete conclusions.\n	&nbsp;\n
 A sustainable data- and AI-literate culture requires supportive communities
 , accessible resources, continuous learning, and shared exploration.\n\n
DTSTART:20260505T111500
SUMMARY:Data Literacy at Vanderbilt: It’s Not a Class…It’s a Culture!
DTEND:20260505T115959
LOCATION: See Description
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