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IoT Data Analytics and Storage

This course will teach you ways to use your live-streams and business data that is being collected by the IoT sensors and devices to their full potential for the betterment of your business.

Self-Paced

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Microsoft

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Intermediate

Difficulty

12 Hours

Course Duration

Course Info

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This course will teach you ways to use your live-streams and business data that is being collected by the IoT sensors and devices to their full potential for the betterment of your business.

Course Information

About this course:

The IoT Data Analytics and Storage course is an integral part of the Certification of Microsoft Professional Program in IoT.

Internet of Things can take your business by a storm, it promises infinite benefits and it can help you discover the true potential of your business data.

This course will teach you ways to use your live-streams and business data that is being collected by the IoT sensors and devices to their full potential for the betterment of your business.

Course Objective:

At the end of the course, students will be able to:

  • Explain typical telemetry data collected by the Azure IoT devices
  • Describe different approaches to analyze IoT data
  • Differentiate between warm and cold storage
  • Way to best use each technology
  • IoT Hub, Data Lake Analytics, and Data Lake Storage
  • Strong concepts of query and analysis of Azure Data Lake sets
  • Describe the benefits of warm storage
  • Differentiate between operational and archive data sets in IoT
  • Configuration and provision of Azure Cosmos Database
  • Integration of Azure Cosmos Database and Azure Stream Analytics
  • Warm storage using IoT data from Cosmos Database
  • Query writing for Cosmos Database
  • Usage of IoT Edge Devices for analysis and action on telemetry data
  • Use cases for analysis on edge devices
  • Edit web-based stream analysis for edge deployment
  • Deployment of analytics on edge devices
  • Deployment of analytics code on edge devices
  • Integrating data stream with data reference data in queries
  • Query writing is various types of Windows time
  • Combining analytics jobs to ensure sophisticated inputs as well as results
  • Employ the best strategies from warm and cold storage with edge analytics to react better to telemetry data
  • Experience of finding solutions based on real-time data

Audience:

The target audience for this course is:

  • IoT Engineers
  • IoT developers

Prerequisite:

Students should be familiar with the following before enrolling for the test:

  • How can IoT help in achieving business goals
  • Ways to establish 2-way communication between real and simulated devices and IoT hub

Outline

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BrandMicrosoft
SubjectsBusiness Productivity, Cloud Computing
Lab AccessNo
TechnologyMicrosoft
Learning StyleSelf-Paced Learning
Learning TypeCourse
DifficultyIntermediate
Course Duration12 Hours
LanguageEnglish

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Course Expert:

Author

Tom Robertson
(Data Science Enthusiast)

Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.

Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.

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