BEGIN:VCALENDAR VERSION:2.0 PRODID:-//ChamberMaster//Event Calendar 2.0//EN METHOD:PUBLISH X-PUBLISHED-TTL:P1H REFRESH-INTERVAL:P1H CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Denver BEGIN:DAYLIGHT RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU DTSTART:20070101T000000 TZOFFSETFROM:-0700 TZOFFSETTO:-0600 TZNAME:Mountain Daylight Time END:DAYLIGHT BEGIN:STANDARD RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU DTSTART:20070101T000000 TZOFFSETFROM:-0600 TZOFFSETTO:-0700 TZNAME:Mountain Standard Time END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/Denver:20190418T073000 DTEND;TZID=America/Denver:20190418T103000 X-MICROSOFT-CDO-ALLDAYEVENT:FALSE SUMMARY:Insights Series | Business Intelligence and Analytics in This Era of Artificial Intelligence DESCRIPTION:Sponsored by In Partnership with \n\nThe CTA Insights Series is a quarterly breakfast that takes a deep dive into an emerging technology topic. The event includes an in-depth presentation from an IDC analyst followed by a panel discussion. Our upcoming Insights Series will focus on Business Intelligence and Analytics in this Era of Artificial Intelligence.Over the past four decades\, majority of Business Intelligence (BI) software has been developed and deployed by not viewing decision making as a process and by equating decision making with information delivery. Traditional BI software solutions do not provide support for all the activities of the decision-making process\, resulting in silos of insight and dependence on specialists. Embedding AI functionality within BI software has the ability to enhance user experience\, improve accessibility to analytics for all knowledge workers while continuing to provide enterprise grade governance and administration. This session will describe the role of artificial intelligence and machine learning in business intelligence\, and explain how enterprises can become more data driven in their decision making.Featuring a demonstration of AWS DeepLens\nApplying machine learning to understand video content in real-time is vital for smart manufacturing\, public safety\, retail\, and other use cases. In this demonstration you'll see how to make use of a machine learning model built in the cloud to detect faces and objects directly on a video device.\n\nAnalyst PresentationChandana Gopal\, Research Director - Business Analytics\, IDC \n\nPanelModerated By Jake Freivald\, VP of Marketing\, Information BuildersRandy DeFauw\, Principal Solutions Architect\, AWSLaura Kornish\, Professor of Marketing and Marketing Division Chair\, Leeds School of Business\, University of Colorado BoulderRachel Mimken\, VP Client Experience\, ChoozleJulius Bogdan\, Director of Analytics and Data Innovation\, SCL Health X-ALT-DESC;FMTTYPE=text/html:
Sponsored by  \;  \;  \;  \;  \;  \; In Partnership with
The CTA Insights Series is a quarterly breakfast that takes a deep dive into an emerging technology topic. The event includes an in-depth presentation from an IDC analyst followed by a panel discussion. Our upcoming Insights Series will focus on Business Intelligence and Analytics in this Era of Artificial Intelligence.
Over the past four decades\, majority of Business Intelligence (BI) software has been developed and deployed by not viewing decision making as a process and by equating decision making with information delivery. Traditional BI software solutions do not provide support for all the activities of the decision-making process\, resulting in silos of insight and dependence on specialists. Embedding AI functionality within BI software has the ability to enhance user experience\, improve accessibility to analytics for all knowledge workers while continuing to provide enterprise grade governance and administration. This session will describe the role of artificial intelligence and machine learning in business intelligence\, and explain how enterprises can become more data driven in their decision making.
Featuring a demonstration of AWS DeepLens
Applying machine learning to understand video content in real-time is vital for smart manufacturing\, public safety\, retail\, and other use cases. In this demonstration you&rsquo\;ll see how to make use of a machine learning model built in the cloud to detect faces and objects directly on a video device.
Analyst Presentation
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Panel