Session Number: 8720
Track: EPM Reporting, BI Analytics, and Data Visualization
Sub-Categorization: BI Analytics
Session Type: Best Practices
Primary Presenter: Tim Vlamis [VP & Analytics Strategist - Vlamis Software Solutions]
Time: Jun 26, 2019 (09:00 AM - 10:00 AM)
Room: 307/308, Level 3
Speaker Bio: As an Oracle ACE and expert in the visualization of data and data science methodologies, Tim Vlamis combines a strong background in the application of Oracle-based machine learning, BI, analytics, and data mining with extensive experience in business modeling and valuation analysis. Tim co-authored Oracle Press’s book titled Data Visualization for Oracle Business Intelligence 11g. He leads the Oracle Advanced Analytics practice in the development of statistical and predictive analytics workflows and processes at Vlamis. He is a credited contributor to Oracle University’s Oracle Data Mining Techniques, Predictive Analytics Using Oracle Data Mining, and Oracle R Enterprise Essentials courses, often serving as an expert instructor for them. Tim’s international business experiences include leading partnership formations and dissolutions in Europe, Australia, Hong Kong, and Canada; negotiating acquisitions in Mexico and Canada; and leading the establishment of a new business entity in India. He earned his Professional Certified Marketer (PCM) designation from the American Marketing Association and served for five years as an adjunct professor of business in Benedictine College’s traditional and executive MBA programs. Tim earned an MBA from Northwestern University’s Kellogg School of Management and a BA in economics from Yale University.
Technologies or Products Used: OBIEE, Data Visualization, Advanced Analytics, BICS,
Session Summary for Attendees: Oracle has placed a major emphasis on machine learning, AI, and predictive analytics. AI is built in to OAC and most other Oracle Cloud products, but do you know how to leverage it? We’ll contrast building machine learning models in data flows in OAC with Oracle Autonomous Data Warehouse Cloud Service. You’ll learn the capabilities and advantages of the different places you can put machine learning models into production. We’ll also cover the business use cases for major machine learning algorithms, such as market segmentation, next-best product recommendations, and production forecasting.