Atlanta Business Intelligence Group

Next Meeting

Monday,

January

07

Predictive Analytics with Power BI

  • In-Person @ 8000 Avalon Boulevard Alpharetta, Georgia, United States (map)
  • 18:30 - 20:30 (UTC-05:00) Eastern Time (US & Canada)
  • Language: English

Sponsor 

Jen Underwood

Jen Underwood <jen@impactanalytix.com>

678-360-3434

Featured Presentation:

Predictive Analytics with Power BI

Teo Lachev, SQL Server MVP Prologika

Predictive analytics, also known as data mining, machine learning, and artificial intelligence (AI), is an increasingly popular requirement. Fortunately, you don't have to be a data scientist to benefit from machine learning in Power BI. This session is organized in two parts: • Part 1 – We will revisit the existing machine learning features in Power BI, including Quick Insights, Explain Increase/Decrease, linear forecasting, integration with R and Python. • Part 2 – We will look at exciting new features that are coming up in near future, such as integration with Azure ML and Cognitive Services, and automated machine learning.

About Teo:
Teo Lachev is an internationally-recognized authority on Data Analytics. Through his Atlanta-based company Prologika, a Microsoft Gold Partner in Data Analytics, he helps organizations make sense of their most valuable asset: their data. His strategy formulation, trusted advisory and mentoring, design and implementation services empower clients to apply effectively data analytics in order to understand, improve, and transform their business processes. Teo has authored and co-authored several bestselling books on organizational and self-service data analytics, and he has been leading the Atlanta Microsoft BI and Power BI group since he founded it in 2010. Teo has been a Microsoft Most Valued Professional (MVP) Data Platform since 2010.

Predictive Analytics with Power BI

Mark Tabladillo, Cloud Solution Architect Microsoft

Predictive analytics, also known as data mining, machine learning, and artificial intelligence (AI), is an increasingly popular requirement. Fortunately, you don't have to be a data scientist to benefit from machine learning in Power BI. This session is organized in two parts: • Part 1 – We will revisit the existing machine learning features in Power BI, including Quick Insights, Explain Increase/Decrease, linear forecasting, integration with R and Python. • Part 2 – We will look at exciting new features that are coming up in near future, such as integration with Azure ML and Cognitive Services, and automated machine learning.

About Mark:
Mark Tabladillo Ph.D. works for Microsoft as a Cloud Solution Architect for the US CTO Customer Success Team. He has a science doctorate from Georgia Tech. Based in Atlanta, GA, Mark provides cloud enterprise solutions for companies in the US for Microsoft's strategic clients. He is a chapter leader for the PASS Data Science virtual chapter. He tweets @marktabnet.

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