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Intelligent Integrations with Azure, Logic Apps and BizTalk

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In this presentation, former BizTalk Premier Field Engineer and BizTastic founder Ricardo Torre shows how to apply machine learning to hybrid integrations using BizTalk, Azure and Logic Apps.

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Intelligent Integrations with Azure, Logic Apps and BizTalk

  1. 1. Intelligent integrations with Azure, Logic Apps and BizTalk Ricardo Torre
  2. 2. Gartner Hype cycle 2017
  3. 3. from Wikipedia • Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.
  4. 4. Agenda • State of Azure Machine Learning • How can we use ML today in your integration scenarios • Applying ML to BizTalk operational data • Applying ML to Logic Apps operational data • Use high level ML (cognitive services)
  5. 5. Azure Machine Learning Studio Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure. • Cloud predictive analytics service • Ready to use algorithms • Quick deploy • Easy drag and drop development • Extend with custom R and Python scripts
  6. 6. Azure Machine Learning Workbench • Integrated, end-to-end data science • Advanced analytics solution • Prepare data, develop experiments, and deploy models • Cloud scale.
  7. 7. Azure Machine Learning Workbench • Visual Studio Code and the AI Extension with Azure Machine Learning Work Bench
  8. 8. How to: ML in your integration scenarios • Actions that can be helped but using ML in integration • Operational • Performance • Anomaly Identification • Preemptive operational actions • Business related actions • How are my orders doing? • Any abnormal behavior up/down stream affecting • Development/Architecture • Business continuity
  9. 9. Applying ML to BizTalk operational data • Using BizTalk Tracking data • Collect and prepare data for Azure ML Experiment Solution • Manually export tracking data • Application Insights/Event Hubs and Stream Insights • Prepare data • Build and deploy model
  10. 10. Anomalies in BizTalk tracking data • Unexpected long processing times • Unhandled Exceptions • Wrong message flow • Changes in volume of messages • Changes message type distribution • Upstream/Downstream inconsistencies
  11. 11. DEMO Detecting anomalies in BizTalk tracking data
  12. 12. Applying ML to Logic Apps operational data • Logic Apps generate a similar tracking information • Data needs preparing • Similar solution can be developed • Automate data collection and ingestion
  13. 13. Use high level ML (cognitive services) • Intelligent algorithms: • See • Hear • Speak • understand and interpret natural communication • Search Transform your business with AI today
  14. 14. DEMO Detecting Faces API
  15. 15. Thank you Ricardo Torre

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