BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260421T185755Z UID:EE338ED6-CD88-416C-B3ED-D05A2679D7A1 DTSTART;TZID=America/Los_Angeles:20260421T090000 DTEND;TZID=America/Los_Angeles:20260421T100000 DESCRIPTION:📊 Data Warehouse for Algorithmic Trading – Student Present ation\n\nEver wondered how financial data is organized and used to support stock market analysis?\n\nJoin this presentation to explore how a Data Wa rehouse system is built to manage and process large-scale stock market dat a. The project demonstrates how raw financial data is transformed into str uctured formats that can be efficiently queried and used for predictive mo delling.\n\n🔍 You’ll learn:\n\n-\nHow Data Warehouses store and organ ize large datasets\n\n-\nStar schema design in a real system\n\n-\nHow dat a pipelines automate transformation of financial data\n\n-\nHow machine le arning models use prepared datasets for predictions\n\n-\nHow large datase ts are processed efficiently\n\n💡 This presentation shows how data syst ems connect directly to real-world applications in finance and computing.\ n\nRoom: HS107\, Bldg: 1000 K. L. O. Rd\, 1000 K. L. O. Rd\, Kelowna\, Bri tish Columbia\, Canada\, V1Y 4X8\, Virtual: https://events.vtools.ieee.org /m/555684 LOCATION:Room: HS107\, Bldg: 1000 K. L. O. Rd\, 1000 K. L. O. Rd\, Kelowna\ , British Columbia\, Canada\, V1Y 4X8\, Virtual: https://events.vtools.iee e.org/m/555684 ORGANIZER:kristina.cormier@myokanagan.bc.ca SEQUENCE:8 SUMMARY:Data Warehouse for Algorithmic Trading Stocks-Price Forecasting on Digital Research Infrastructure using Machine Learning Modelling URL;VALUE=URI:https://events.vtools.ieee.org/m/555684 X-ALT-DESC:Description: <br /><p id="docs-internal-guid-882b6937-7fff-e6d9- 7618-804bb4ad2237" dir="ltr" style="line-height: 1.38\; margin-top: 12pt\; margin-bottom: 12pt\;"><span style="font-size: 11pt\; font-family: Arial\ ,sans-serif\; color: #000000\; background-color: transparent\; font-weight : bold\; font-style: normal\; font-variant: normal\; text-decoration: none \; vertical-align: baseline\; white-space: pre-wrap\;">📊 Data Warehouse for Algorithmic Trading &ndash\; Student Presentation</span></p>\n<p dir= "ltr" style="line-height: 1.38\; margin-top: 12pt\; margin-bottom: 12pt\;" ><span style="font-size: 11pt\; font-family: Arial\,sans-serif\; color: #0 00000\; background-color: transparent\; font-weight: 400\; font-style: nor mal\; font-variant: normal\; text-decoration: none\; vertical-align: basel ine\; white-space: pre-wrap\;">Ever wondered how financial data is organiz ed and used to support stock market analysis?</span></p>\n<p dir="ltr" sty le="line-height: 1.38\; margin-top: 12pt\; margin-bottom: 12pt\;"><span st yle="font-size: 11pt\; font-family: Arial\,sans-serif\; color: #000000\; b ackground-color: transparent\; font-weight: 400\; font-style: normal\; fon t-variant: normal\; text-decoration: none\; vertical-align: baseline\; whi te-space: pre-wrap\;">Join this presentation to explore how a Data Warehou se system is built to manage and process large-scale stock market data. Th e project demonstrates how raw financial data is transformed into structur ed formats that can be efficiently queried and used for predictive modelli ng.</span></p>\n<p dir="ltr" style="line-height: 1.38\; margin-top: 12pt\; margin-bottom: 12pt\;"><span style="font-size: 11pt\; font-family: Arial\ ,sans-serif\; color: #000000\; background-color: transparent\; font-weight : 400\; font-style: normal\; font-variant: normal\; text-decoration: none\ ; vertical-align: baseline\; white-space: pre-wrap\;">🔍 </span><span st yle="font-size: 11pt\; font-family: Arial\,sans-serif\; color: #000000\; b ackground-color: transparent\; font-weight: bold\; font-style: normal\; fo nt-variant: normal\; text-decoration: none\; vertical-align: baseline\; wh ite-space: pre-wrap\;">You&rsquo\;ll learn:</span></p>\n<ul style="margin- top: 0\; margin-bottom: 0\; padding-inline-start: 48px\;">\n<li dir="ltr" style="list-style-type: disc\; font-size: 11pt\; font-family: Arial\,sans- serif\; color: #000000\; background-color: transparent\; font-weight: 400\ ; font-style: normal\; font-variant: normal\; text-decoration: none\; vert ical-align: baseline\; white-space: pre\;" aria-level="1">\n<p dir="ltr" s tyle="line-height: 1.38\; margin-top: 12pt\; margin-bottom: 0pt\;" role="p resentation"><span style="font-size: 11pt\; font-family: Arial\,sans-serif \; color: #000000\; background-color: transparent\; font-weight: 400\; fon t-style: normal\; font-variant: normal\; text-decoration: none\; vertical- align: baseline\; white-space: pre-wrap\;">How Data Warehouses store and o rganize large datasets</span></p>\n</li>\n<li dir="ltr" style="list-style- type: disc\; font-size: 11pt\; font-family: Arial\,sans-serif\; color: #00 0000\; background-color: transparent\; font-weight: 400\; font-style: norm al\; font-variant: normal\; text-decoration: none\; vertical-align: baseli ne\; white-space: pre\;" aria-level="1">\n<p dir="ltr" style="line-height: 1.38\; margin-top: 0pt\; margin-bottom: 0pt\;" role="presentation"><span style="font-size: 11pt\; font-family: Arial\,sans-serif\; color: #000000\; background-color: transparent\; font-weight: 400\; font-style: normal\; f ont-variant: normal\; text-decoration: none\; vertical-align: baseline\; w hite-space: pre-wrap\;">Star schema design in a real system</span></p>\n</ li>\n<li dir="ltr" style="list-style-type: disc\; font-size: 11pt\; font-f amily: Arial\,sans-serif\; color: #000000\; background-color: transparent\ ; font-weight: 400\; font-style: normal\; font-variant: normal\; text-deco ration: none\; vertical-align: baseline\; white-space: pre\;" aria-level=" 1">\n<p dir="ltr" style="line-height: 1.38\; margin-top: 0pt\; margin-bott om: 0pt\;" role="presentation"><span style="font-size: 11pt\; font-family: Arial\,sans-serif\; color: #000000\; background-color: transparent\; font -weight: 400\; font-style: normal\; font-variant: normal\; text-decoration : none\; vertical-align: baseline\; white-space: pre-wrap\;">How data pipe lines automate transformation of financial data</span></p>\n</li>\n<li dir ="ltr" style="list-style-type: disc\; font-size: 11pt\; font-family: Arial \,sans-serif\; color: #000000\; background-color: transparent\; font-weigh t: 400\; font-style: normal\; font-variant: normal\; text-decoration: none \; vertical-align: baseline\; white-space: pre\;" aria-level="1">\n<p dir= "ltr" style="line-height: 1.38\; margin-top: 0pt\; margin-bottom: 0pt\;" r ole="presentation"><span style="font-size: 11pt\; font-family: Arial\,sans -serif\; color: #000000\; background-color: transparent\; font-weight: 400 \; font-style: normal\; font-variant: normal\; text-decoration: none\; ver tical-align: baseline\; white-space: pre-wrap\;">How machine learning mode ls use prepared datasets for predictions</span></p>\n</li>\n<li dir="ltr" style="list-style-type: disc\; font-size: 11pt\; font-family: Arial\,sans- serif\; color: #000000\; background-color: transparent\; font-weight: 400\ ; font-style: normal\; font-variant: normal\; text-decoration: none\; vert ical-align: baseline\; white-space: pre\;" aria-level="1">\n<p dir="ltr" s tyle="line-height: 1.38\; margin-top: 0pt\; margin-bottom: 12pt\;" role="p resentation"><span style="font-size: 11pt\; font-family: Arial\,sans-serif \; color: #000000\; background-color: transparent\; font-weight: 400\; fon t-style: normal\; font-variant: normal\; text-decoration: none\; vertical- align: baseline\; white-space: pre-wrap\;">How large datasets are processe d efficiently</span></p>\n</li>\n</ul>\n<p dir="ltr" style="line-height: 1 .38\; margin-top: 12pt\; margin-bottom: 12pt\;"><span style="font-size: 11 pt\; font-family: Arial\,sans-serif\; color: #000000\; background-color: t ransparent\; font-weight: 400\; font-style: normal\; font-variant: normal\ ; text-decoration: none\; vertical-align: baseline\; white-space: pre-wrap \;">💡 This presentation shows how data systems connect directly to real -world applications in finance and computing.</span><span style="font-size : 11pt\; font-family: Arial\,sans-serif\; color: #000000\; background-colo r: transparent\; font-weight: 400\; font-style: normal\; font-variant: nor mal\; text-decoration: none\; vertical-align: baseline\; white-space: pre- wrap\;"> </span></p> END:VEVENT END:VCALENDAR