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Applied Azure Internet of Things (IoT) Scenarios with Real Time R Analysis by Noam Arnold

Applied Azure Internet of Things (IoT) Scenarios with Real Time R Analysis by Noam Arnold

In this session, Noam presents approaches to building IoT architectures in Azure. He teaches us the lessons that they learned in real-world large scale IoT customer projects and how they dealt with the challenges that came up. The second part of the presentation covers how Data Science approaches can be used to analyze the real time data using R and stream analytics.

Speaker: Noam Arnold, Trivadis AG
Noam started his career in IT after he finished his studies in mathematics at UZH. He works as a Business Intelligence consultant at Trivadis and has a strong focus on Sql, Mdx, PowerPivot, Power BI and Data Science in the Microsoft Azure Cloud.

Azure Zurich User Group
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October 26, 2017
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Transcript

  1. BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG

    COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH Applied Azure Internet of Things Scenarios with Real Time R Analysis Noam Arnold Azure Data Science Night 26.10.2017 http://www.azurezurichusergroup.com
  2. Agenda 27.10.2017 1. How it started ... 2. The IoTgate

    3. Customer Stories 4. Data Science
  3. 27.10.2017 How it started ...

  4. "Collecting data and providing it for further utilization is one

    of the major challenges in the energy sector. The use of IoT technology allows us to build customer- and near-time solutions which are cost- effective, powerful and expandable.“ René Frei, Head of ICT, Industrielle Werke Basel 27.10.2017
  5. 27.10.2017

  6. Challenge Devices Sources Business Applications 27.10.2017

  7. intelligent asset management (IoT Windpark) 27.10.2017

  8. Findings - Solarpark 27.10.2017

  9. Findings – Windturbine foundation 27.10.2017

  10. 27.10.2017

  11. Findings – Windfarm gearbox failure 27.10.2017

  12. Gridbox exchange 27.10.2017

  13. 27.10.2017

  14. 27.10.2017

  15. gate 27.10.2017

  16. measure send Live Power BI Dashboard Azure SQL DB Azure

    Data Lake Pull Push collect buffer Stream Analytics Push distribute transform archive illustrate Power BI / Excel Pull Pull analyse Machine Learning Pull & Push Event Hub Push Pull Application IoT Hub Push Writeback Event Hub Push Pull MDS Meta-data management Devices 27.10.2017
  17. Demo: Reporting Cockpit 27.10.2017

  18. 27.10.2017 Customer Projects

  19. Smart City IoTgate Lärmmessungen Grundwasser Wasser - Labordaten 27.10.2017

  20. IoT @ gas stations & fuel tanks 27.10.2017 1 pro

    h 8:00 Uhr disponiert
  21. IoT @ gas stations & fuel tanks IoTgate 27.10.2017 15

    min. Takt
  22. 27.10.2017

  23. 27.10.2017

  24. IoT @ gas stations & fuel tanks IoTgate 27.10.2017

  25. IoT @ gas stations & fuel tanks IoTgate 27.10.2017 Sekunden

    Takt?
  26. 27.10.2017 Data Science With Microsoft Azure

  27. 27.10.2017

  28. 27.10.2017

  29. 27.10.2017

  30. 27.10.2017

  31. 27.10.2017

  32. April 6, 2015 “This acquisition will help customers use advanced

    analytics within Microsoft data platforms.“
  33. Agenda On Premises Cloud Desktop Server Power BI R Studio

    R Tools for Visual Studio Power BI R Server SQL Server R Services Azure ML
  34. Agenda On Premises Cloud Desktop Server Power BI R Studio

    R Tools for Visual Studio Power BI R Server SQL Server R Services Azure ML
  35. Agenda On Premises Cloud Desktop Server Power BI R Studio

    R Tools for Visual Studio Power BI R Server SQL Server R Services Azure ML
  36. measure send Live Power BI Dashboard Azure SQL DB Azure

    Data Lake Pull Push collect buffer Stream Analytics Push distribute transform archive illustrate Power BI / Excel Pull Pull analyse Machine Learning Pull & Push Event Hub Push Pull Application IoT Hub Push Writeback Event Hub Push Pull MDS Meta-data management Devices 27.10.2017
  37. measure send Live Power BI Dashboard Azure SQL DB Azure

    Data Lake Pull Push collect buffer Stream Analytics Push distribute transform archive illustrate Power BI / Excel Pull Pull analyse Machine Learning Pull & Push Event Hub Push Pull Application IoT Hub Push Writeback Event Hub Push Pull MDS Meta-data management Devices 27.10.2017 Machine Learning
  38. Questions & Anwsers ... Noam Arnold [email protected] 27.10.2017