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PASS BA Virtual Chapter Presents: “Rise of the Machine (Learning)” November 18, 2015 Email - passbavc@sqlpass.orgpassbavc@sqlpass.org
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PASS Business Analytics Virtual Chapter Chapter Leader – Dan English Dan is a Microsoft SQL Server MVP, author, on the leadership team for the MN Microsoft BI User Group, and is the Senior Data Warehouse Architect at Constellation, Inc. in MN. Chapter Co-Leader – Paras Doshi Paras started out with the chapter as VP of marketing helping double the membership base in 9 months and then transitioned into his current leadership role. Paras is passionate about helping businesses extract valuable insights from data and currently works as BI Architect at Thomas Jefferson University Hospitals PASS Business Analytics Virtual Chapter http://tinyurl.com/linkedinpassbavc https://twitter.com/passbavc Twitter handle @passbavc http://www.youtube.com/user/PASSBAVC YouTube Channel
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Select Virtual Chapter Meetings more events and info at sqlpass.org/events VIRTUAL CHAPTERMEETINGTOPIC VirtualizationNov 18 12:00-13:00 UTC-05:00Architecting Virtual Environments for Business Intelligence Global SpanishNov 18 12:00-13:00 UTC-05:00JSON Support en SQL Server 2016 presented by Carlos Andres Ulate Hernandez Business AnalyticsNov 18 12:00-13:00 UTC-05:00Rise of the Machine (Learning) – Azure ML in BI, in Apps, and as a product in Azure Marketplace presented by Greg Beaumont HealthcareNov 19 13:00-14:00 UTC-05:00Health Plan – Payer Analytics: Uncover Insights, Reveal Trends, and Take Action presented by Carrie Nielsen PerformanceNov 19 14:00-15:00 UTC-05:00Optimizing your data warehouse for OLAP Processing presented by Konstantin Melamud Saturday Night SQLNov 21 21:00-22:00 UTC-05:00Reporting Tool Efficiency Discussion Global SpanishNov 25 12:00-13:00 UTC-05:00Vista 360 grados de DataZen presented by Juan Alvarado
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Upcoming SQLSaturdays North America International Nov 21Montreal Nov 21 Salt Lake City Dec 5Washington DC Dec 12 Providence Jan 9Atlanta BI Edition Jan 16 Nashville Jan 30Austin Nov 21Madrid Nov 21 Costa Rica BI Nov 21Brasilia Nov 28Mexico City Nov 28Parma Nov 28 Belgrade Dec 5Lima Dec 5Southampton Visit www.sqlsaturday.com to register for a event near you! www.sqlsaturday.com
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6 Volunteering Opportunities PASS would not exist without passionate, dedicated, and hardworking volunteers from around the globe. Volunteer today!! For local opportunities please visit volunteer.sqlpass.org For PASS HQ related activities, please update the “MyVolunteering” section of your MyPASS profile.
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Stay Involved! Sign up for a free membership today at sqlpass.org Linked In: http://www.sqlpass.org/linkedinhttp://www.sqlpass.org/linkedin Facebook: http://www.sqlpass.org/facebookhttp://www.sqlpass.org/facebook Twitter: @SQLPASS #sqlpass PASS: http://www.sqlpass.orghttp://www.sqlpass.org
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November 18 – Rise of the Machine (Learning) Abstract Machine Learning no longer requires expensive infrastructures and knowledge of specialized statistical coding languages. Azure ML lowers the barriers of entry for predictive analytics using Machine Learning. In this session, review the similarities and differences of Machine Learning compared to traditional Predictive Analytics, Data Mining, Data Science, and Artificial Intelligence. Learn how to integrate predictive analytics into your existing analytics and reporting strategy and infrastructure. I will demonstrate how a BI solution using only Excel with Power Pivot can connect to an Azure ML Model in the cloud for predictions and new types of analysis. Learn how Azure ML can be used to add value to Apps. Also, review ways to turn your Azure ML Model into a source of revenue using Azure Marketplace. Machine Learning is now quietly rising all around us as it integrates with technology, improves processes and workflows, and transforms how data drives business. Empower your organization with new competitive advantages using Azure ML. Presenter Greg Beaumont has been working as a consultant using Microsoft BI tools since 2007, and I have experience with a wide array of industry verticals including but not limited to healthcare, manufacturing, Government, and Six Sigma. My preferred areas of focus are Data Science, data visualization, data modeling, and designing analytic solutions.
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