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    <title>DAMA-Toronto IRMAC upcoming events</title>
    <link>https://www.irmac.ca/events-home</link>
    <description>DAMA-Toronto IRMAC upcoming events</description>
    <dc:creator>DAMA-Toronto IRMAC</dc:creator>
    <generator>Wild Apricot - membership management software and more</generator>
    <language>en</language>
    <pubDate>Tue, 01 Sep 2026 07:22:26 GMT</pubDate>
    <lastBuildDate>Tue, 01 Sep 2026 07:22:26 GMT</lastBuildDate>
    <item>
      <pubDate>Fri, 18 Sep 2026 12:30:00 GMT</pubDate>
      <title>Introduction to building Data Foundations: From Messy Data to Scalable Analytics (Semantic Modelling Workshop) (18 Sep 2026)</title>
      <description>&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;" color="#333333"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif" style=""&gt;This is a SPECIAL&lt;/font&gt;&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;All-Day workshop&lt;/font&gt;&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;and networking event that will walk participants through the core building blocks of modern data foundations, from architecture and modeling to shared definitions and AI-ready design. This is a uniquely exciting opportunity for those looking to understand and modernize their data infrastructure in finding new ways at building trust in your data across your organization.&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;" color="#333333"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;This event is supported by the&lt;/font&gt;&lt;/span&gt; &lt;a href="https://www.malloydata.dev/"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;Malloy open-source project&lt;/font&gt;&lt;/span&gt;&lt;/a&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;and its contributors (&lt;/font&gt;&lt;/span&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;Google's Looker Cofounder&lt;/font&gt;&lt;/span&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;: Lloyd Tabb and Michael Toy). This event is also supported by&lt;/font&gt;&lt;/span&gt; &lt;a href="https://credibledata.com"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;https://credibledata.com&lt;/font&gt;&lt;/span&gt;&lt;/a&gt;&amp;nbsp;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;engine.&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;" color="#333333"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;This interactive workshop is&lt;/font&gt;&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;designed for people who work with data, rely on data, or are responsible for data outcomes.&lt;/font&gt;&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;ex. Leaders impacting Data Strategy, Data Product Managers, Data Project Managers, Data Engineers, Aspiring Data Persons, Data Analysts, Data Scientists, Data Strategy Roles, Data Program Managers, Non-Profit Technical Teams or Data Teams, etc.&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;" color="#333333"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;&lt;em&gt;Note: This workshop's title is updated from Semantic Modelling workshop to better reflect the objective of the workshop&lt;/em&gt;&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif" style="font-size: 16px;" color="#333333"&gt;&lt;strong&gt;Why attend this event?&lt;/strong&gt;&lt;/font&gt;&lt;/span&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif" style="font-size: 16px;" color="#333333"&gt;This event is important because most organizations don’t struggle because they lack data, they struggle because they can’t trust it.&lt;/font&gt;&lt;/span&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif" style="font-size: 16px;" color="#333333"&gt;One dashboard says revenue is up, another says it’s down. Teams spend meetings debating numbers instead of making decisions. Reports break when systems change. AI tools and Copilots promise insights but produce answers no one feels confident acting on.&lt;/font&gt;&lt;/span&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;" color="#333333"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;This workshop breaks down (in plain language)&lt;/font&gt;&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;why these problems happen&lt;/font&gt;&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;and&lt;/font&gt;&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;how modern organizations are able to design data foundations to avoid them&lt;/font&gt;&lt;/span&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;. You’ll see practical examples of how inconsistent definitions, poorly designed reporting layers, and missing shared context lead to confusion, rework, and stalled initiatives.&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif" style="font-size: 16px;" color="#333333"&gt;By the end of the day, you’ll understand how data should be structured so the same numbers mean the same thing everywhere, new reports can be built without starting from scratch, and analytics and AI can be safely layered on as your organization grows without constant firefighting.&lt;/font&gt;&lt;/span&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font color="#333333" face="Arial, sans-serif"&gt;&lt;span style="font-size: 16px;"&gt;Still need more details? Please visit this page to watch the overview of the workshop provided by one of the speakers, Miles Garvey here :&lt;a href="https://irmac.wildapricot.org/page-18224" target="_blank"&gt;Past Presentations - Open to All&lt;/a&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;" color="#333333"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;8:30 am – 3:00 pm; Format&lt;/font&gt;&lt;/span&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;: Day workshop with structured networking;&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;" color="#333333"&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;Catering&lt;/font&gt;&lt;/span&gt;&lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;: Coffee on arrival + light lunch provided&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;span style=""&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 16px;"&gt;&lt;strong&gt;Agenda:&amp;nbsp;&lt;/strong&gt;&lt;/font&gt;&lt;/span&gt;&lt;/p&gt;

&lt;ul style="line-height: 20px;"&gt;
  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;8:30 – 9:00 Coffee &amp;amp; Networking (30 min) Open Seating&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;9:00 – 9:15 Welcome &amp;amp; Context (15 min)&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font style="font-size: 14px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;span style=""&gt;9:15 – 10:15&lt;/span&gt; &lt;span style=""&gt;Modern Data Architecture Fundamentals&lt;/span&gt; &lt;span style=""&gt;(45-60 min) by&amp;nbsp;&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;span style=""&gt;Dil Mustafa&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;10:15 – 10:30 Networking Break (15 min)&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font style="font-size: 14px;"&gt;&lt;font color="#373737"&gt;&lt;font color="#373737"&gt;&lt;span style=""&gt;10:30 – 11:30&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;The Data Gold Layer Fundamentals &amp;amp; How to Compose It&lt;/font&gt;&lt;font face="Arial, sans-serif"&gt;&amp;nbsp;&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;span style=""&gt;Workshop&lt;/span&gt; &lt;span style=""&gt;(60 min) by Suraj Lamgaday&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font face="Arial, sans-serif"&gt;&lt;font face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style="color: rgb(55, 55, 55);"&gt;11:30 – 11:45&lt;/span&gt; &lt;span style=""&gt;&lt;font style="" color="#333333"&gt;Networking Break + Seat Rotation&lt;/font&gt;&lt;/span&gt; &lt;span style="color: rgb(55, 55, 55);"&gt;(15 min)&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font style="font-size: 14px;"&gt;&lt;font color="#373737"&gt;&lt;font color="#373737"&gt;&lt;span style=""&gt;11:45 – 12:45&lt;/span&gt; &lt;span style=""&gt;Data Semantic/Self-Service Design and Background&lt;/span&gt; &lt;span style=""&gt;&lt;font face="Arial, sans-serif"&gt;(60 min) by&lt;/font&gt;&lt;font face="Arial, sans-serif"&gt;&amp;nbsp;&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;span style=""&gt;Miles Garvey&amp;nbsp;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;12:45 – 1:15 Light Lunch &amp;amp; Networking (30 min)&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;1:15 - 1:45&lt;/span&gt; &lt;span style=""&gt;Semantic Design Workshop&amp;nbsp;&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;1:45 - 2:45&lt;/span&gt; &lt;span style=""&gt;Data Design and ROI for AI Understanding&lt;/span&gt; &lt;span style=""&gt;(60 min)&amp;nbsp; by Kyle Nesbit&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;2:45 – 3:00&lt;/span&gt; &lt;span style=""&gt;Interactive Group Session&lt;/span&gt; &lt;span style=""&gt;(15 min)&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p style="line-height: 31px;"&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;font color="#373737" face="Arial, sans-serif" style="font-size: 14px;"&gt;&lt;span style=""&gt;3:05 – 3:15 Ending Remarks (10 min)&lt;/span&gt;&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;
&lt;/ul&gt;&lt;font color="#373737" face="Arial, sans-serif, WaWebKitSavedSpanIndex_54, WaWebKitSavedSpanIndex_55"&gt;&lt;strong&gt;Hurry, Limited seats and Early bird pricing is available only for a short time!!&lt;/strong&gt;&lt;/font&gt;

&lt;ul style="line-height: 20px;"&gt;&lt;/ul&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;"&gt;&lt;span style=""&gt;&lt;font color="#373737" face="Arial, sans-serif"&gt;&lt;img 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" width="81" height="25"&gt;&lt;/font&gt;&lt;/span&gt;&lt;span style=""&gt;&lt;font color="#000000" face="Arial, sans-serif"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/font&gt;&lt;/span&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;"&gt;&lt;a href="http://linkedin.com/in/miles-garvey-475049189"&gt;&lt;span style=""&gt;&lt;font color="#008BAE" face="Arial, sans-serif"&gt;Miles Garvey&lt;/font&gt;&lt;/span&gt;&lt;/a&gt;&lt;font color="#000000" face="Roboto, sans-serif"&gt;is a modern data strategist with cross-sector experience spanning public institutions, consulting, and high-growth private companies. With a background rooted in analytics engineering and data infrastructure, he has helped organizations evolve from fragmented reporting cultures into insight-driven, self-service ecosystems. Miles brings a holistic understanding of how data works in the real world. He speaks frequently about the evolving role of analytics teams, the future of data ownership, and how organizations can adopt AI-native infrastructure.&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;span style=""&gt;&lt;font color="#000000" face="Roboto, sans-serif" style="font-size: 16px;"&gt;Most recently in the private sector, he led analytics and data platform initiatives at G2, where he built scalable data pipelines, implemented semantic layers, and AI-integrated analytics. Currently, Miles runs his own data advisory consultancy spanning larger institutions.&lt;/font&gt;&lt;/span&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;"&gt;&lt;a href="https://www.linkedin.com/in/dil-mustafa-383725163/"&gt;&lt;span style=""&gt;&lt;font color="#1155CC" face="Arial, sans-serif"&gt;Dil Mustafa&lt;/font&gt;&lt;/span&gt;&lt;/a&gt;&lt;font color="#000000" face="Roboto, sans-serif"&gt;Dil Mustafa is a Data and AI architect and former data leader at Best Buy, focused on building scalable data platforms and warehouses that support reliable analytics and decision-making.&amp;nbsp; He specializes in designing end-to-end data architectures (from ingestion to modeling and semantic layers) helping organizations move from fragmented reporting to trusted, reusable data.&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font color="#000000" face="Roboto, sans-serif" style="font-size: 16px;"&gt;Dil has led 20+ data and AI initiatives, improving data consistency, reducing duplication, and enabling teams to work from a shared foundation. He emphasizes clear modeling, strong governance, and practical, maintainable design.&amp;nbsp; Based in Canada, he is currently an Enterprise Data and AI Architect at Datavise Consulting Inc., with previous experience at WestJet and Cenovus Energy.&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;"&gt;&lt;a href="http://linkedin.com/in/lamgaday"&gt;&lt;span style=""&gt;&lt;font color="#008BAE" face="Arial, sans-serif"&gt;Suraj Lamgaday&lt;/font&gt;&lt;/span&gt;&lt;/a&gt;&lt;font color="#000000" face="Roboto, sans-serif"&gt;&amp;nbsp;is a Data Lead at G2, where he leads the implementation of the company’s Golden Layer data architecture. He has helped build multi-million-dollar lines of business using data, developed full-stack analytics products for institutional investors, and partnered closely with business teams to turn raw data into trusted decision systems.&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font color="#000000" face="Roboto, sans-serif" style="font-size: 16px;"&gt;Prior to G2, Suraj overhauled enterprise data architecture and semantic layers at a top ten U.S. law firm and previously worked at JPMorgan Chase, contributing to Golden Layer initiatives across Asset Management and Commercial Banking. His work centers on building scalable, business-ready data foundations that organizations can rely on.&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font style="font-size: 16px;"&gt;&lt;a href="http://linkedin.com/in/kyle-nesbit-7312a58"&gt;&lt;span style=""&gt;&lt;font color="#008BAE" face="Arial, sans-serif"&gt;Kyle Nesbit&lt;/font&gt;&lt;/span&gt;&lt;/a&gt; &lt;font color="#000000" face="Roboto, sans-serif"&gt;is the Founder &amp;amp; CEO of&lt;/font&gt; &lt;a href="https://credibledata.com/"&gt;&lt;font color="#000000" face="Roboto, sans-serif"&gt;Credible&lt;/font&gt;&lt;/a&gt;&lt;font color="#000000" face="Roboto, sans-serif"&gt;, a platform for engineering and delivering shared meaning across enterprise data. He’s a technical founder and engineering leader focused on semantic modeling, context systems, and AI-first developer workflows.&lt;/font&gt;&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font color="#000000" face="Roboto, sans-serif" style="font-size: 16px;"&gt;Prior to Credible, Kyle spent 17 years at Google, where he worked on high-performance distributed systems, machine learning in ads, and AI-powered analytics. He helped build core infrastructure behind BigQuery and later worked on bringing generative AI capabilities into Looker following Google’s acquisition. He also spent time with Gradient Ventures, Google’s AI-focused venture fund, gaining perspective on what makes AI systems scalable, reliable, and investable.&lt;/font&gt;&lt;/p&gt;

&lt;p style="line-height: 20px;"&gt;&lt;font color="#000000" face="Roboto, sans-serif" style="font-size: 16px;"&gt;At Credible, Kyle is pioneering Engineering Meaning: treating business intent, definitions, and relationships as first-class, versioned, testable assets and delivering that meaning in context to analytics, applications, and AI systems.&lt;/font&gt;&lt;/p&gt;</description>
      <link>https://irmac.wildapricot.org/event-6766719</link>
      <guid>https://irmac.wildapricot.org/event-6766719</guid>
      <dc:creator />
    </item>
    <item>
      <pubDate>Thu, 22 Oct 2026 12:00:00 GMT</pubDate>
      <title>DAMA Days Toronto 2026 (22 Oct 2026)</title>
      <description>&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;DAMA Toronto’s flagship annual conference returns on &lt;strong&gt;October 22&lt;/strong&gt;—this year as a &lt;strong&gt;single, high‑impact full day&lt;/strong&gt; designed to bring the GTA data community together for learning, connection, and practical insights you can apply immediately.&lt;/font&gt;&lt;/p&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;From a morning keynote through expert‑led sessions, a panel discussion, and a closing networking reception, DAMA Days delivers a full arc of professional development and community building.&lt;/font&gt;&lt;/p&gt;

&lt;h2&gt;&lt;strong style=""&gt;&lt;font face="Helvetica" style="font-size: 18px;"&gt;Who should Attend&lt;/font&gt;&lt;/strong&gt;&lt;/h2&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;Data management, Analytics. AI and Data Governance professionals across the GTA, including:&lt;/font&gt;&lt;/p&gt;

&lt;ul style="font-size: 18px;"&gt;
  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;Practitioners and leaders from private and public sectors&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;Consultants, vendors, and solution providers&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;Students, early‑career professionals, and CDMP candidates&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;Anyone passionate about advancing data management practices&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;
&lt;/ul&gt;

&lt;h2 style="font-size: 18px;"&gt;&lt;strong&gt;&lt;font face="Helvetica"&gt;International Guests &amp;amp; DAMA Leaders&lt;/font&gt;&lt;/strong&gt;&lt;/h2&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;This year, we are proud to welcome &lt;strong&gt;international data professionals from DAMA International&lt;/strong&gt;, including:&lt;/font&gt;&lt;/p&gt;

&lt;ul style="font-size: 18px;"&gt;
  &lt;li&gt;
    &lt;p&gt;&lt;strong&gt;&lt;a href="https://www.linkedin.com/in/petervennel/" target="_blank"&gt;&lt;font face="Helvetica"&gt;Peter Vennel&lt;/font&gt;&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;strong&gt;&lt;a href="https://www.linkedin.com/in/fkadwell/" target="_blank"&gt;&lt;font face="Helvetica"&gt;Frank Kadwell&lt;/font&gt;&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;strong&gt;&lt;a href="https://www.linkedin.com/in/peteraiken/" target="_blank"&gt;&lt;font face="Helvetica"&gt;Peter Aiken&lt;/font&gt;&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;strong&gt;&lt;a href="https://www.linkedin.com/in/aakritiagrawal/" target="_blank"&gt;&lt;font face="Helvetica"&gt;Aakriti Agrawal Kim&lt;/font&gt;&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;strong&gt;&lt;a href="https://www.linkedin.com/in/ellen-mildred-brown/" target="_blank"&gt;&lt;font face="Helvetica"&gt;Ellen Brown&lt;/font&gt;&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;strong&gt;&lt;a href="https://www.linkedin.com/in/marilul/" target="_blank"&gt;&lt;font face="Helvetica"&gt;Marilu Lopez&lt;/font&gt;&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;
  &lt;/li&gt;
&lt;/ul&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;Several of these distinguished leaders will also be &lt;strong&gt;presenting at the conference&lt;/strong&gt;, bringing global perspectives, deep expertise, and thought leadership directly to our Toronto community.&lt;/font&gt;&lt;/p&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;Their participation elevates DAMA Days 2026 into a truly international gathering of data management excellence.&lt;/font&gt;&lt;/p&gt;

&lt;h2 style="font-size: 18px;"&gt;&lt;strong&gt;&lt;font face="Helvetica"&gt;What to Expect in 2026&lt;/font&gt;&lt;/strong&gt;&lt;/h2&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;We are currently finalizing our &lt;strong&gt;speaker lineup and session topics&lt;/strong&gt;, and this year’s program is shaping up to offer even more value, connection, and opportunities for data professionals.&lt;/font&gt;&lt;/p&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;Planned highlights include:&lt;/font&gt;&lt;/p&gt;

&lt;ul style="font-size: 18px;"&gt;
  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Keynote and expert-led sessions&lt;/strong&gt; on best Data Management practices&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Panel discussions&lt;/strong&gt; featuring leaders across industries&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Vendor showcase&lt;/strong&gt; with opportunities to explore tools, platforms, and services&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Complimentary professional headshots&lt;/strong&gt; for all attendees&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Exclusive discounts&lt;/strong&gt; on literature authored by industry experts&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Networking opportunities&lt;/strong&gt; with:&lt;/font&gt;&lt;/p&gt;

    &lt;ul&gt;
      &lt;li&gt;
        &lt;p&gt;&lt;font face="Helvetica"&gt;Local data management professionals from across the GTA&lt;/font&gt;&lt;/p&gt;
      &lt;/li&gt;

      &lt;li&gt;
        &lt;p&gt;&lt;font face="Helvetica"&gt;Leaders from both private and public sectors&lt;/font&gt;&lt;/p&gt;
      &lt;/li&gt;

      &lt;li&gt;
        &lt;p&gt;&lt;font face="Helvetica"&gt;Subject matter experts spanning technical and business perspectives&lt;/font&gt;&lt;/p&gt;
      &lt;/li&gt;

      &lt;li&gt;
        &lt;p&gt;&lt;font face="Helvetica"&gt;Local nonprofits and community organizations making an impact in data management&lt;/font&gt;&lt;/p&gt;
      &lt;/li&gt;
    &lt;/ul&gt;
  &lt;/li&gt;
&lt;/ul&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;As planning progresses, some program details may be updated. The agenda will continue to evolve as speakers and topics are confirmed.&lt;/font&gt;&lt;/p&gt;

&lt;h2 style="font-size: 18px;"&gt;&lt;strong&gt;&lt;font face="Helvetica"&gt;Pricing &amp;amp; Sponsorship&lt;/font&gt;&lt;/strong&gt;&lt;/h2&gt;

&lt;ul style="font-size: 18px;"&gt;
  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Member and early‑bird pricing&lt;/strong&gt; available&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;

  &lt;li&gt;
    &lt;p&gt;&lt;font face="Helvetica"&gt;&lt;strong&gt;Sponsorship opportunities&lt;/strong&gt; for organizations looking to showcase their brand to a highly engaged data audience&lt;/font&gt;&lt;/p&gt;
  &lt;/li&gt;
&lt;/ul&gt;

&lt;p style="font-size: 18px;"&gt;&lt;font face="Helvetica"&gt;To learn more about sponsorship packages, please contact &lt;strong&gt;sapna.jain@irmac.ca&lt;/strong&gt;.&lt;/font&gt;&lt;/p&gt;</description>
      <link>https://irmac.wildapricot.org/event-6782011</link>
      <guid>https://irmac.wildapricot.org/event-6782011</guid>
      <dc:creator />
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