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Operationalize Cloud Analytics Solutions with Microsoft Azure (55224-2)

$1,195.00 $775.00

This is a two-day instructor-led course intended for data professionals who want to expand their knowledge about creating big data analytic solutions on Microsoft Azure. Students will learn how to operationalize end-to-end cloud analytics solutions using the Azure Portal and Azure PowerShell. It can be used on its own or with 55224-1, Microsoft Azure Big Data Analytics, to prepare for exam 70-475.



Description

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Course: 55224-2 – Operationalize Cloud Analytics Solutions with Microsoft Azure

This is a two-day instructor-led course intended for data professionals who want to expand their knowledge about creating big data analytic solutions on Microsoft Azure. Students will learn how to operationalize end-to-end cloud analytics solutions using the Azure Portal and Azure PowerShell. It can be used on its own or with 55224-1, Microsoft Azure Big Data Analytics, to prepare for exam 70-475.

Audience profile

This course is intended for experienced data professionals who design and build big data analytics solutions on Microsoft Azure.

At course completion

After completing this course, students will be able to:

  • Create a Data Factory
  • Orchestrate data processing activities in a data-driven workflow
  • Monitor and Manage a Data Factory
  • Move, Transform or Analyze data
  • Design a deployment strategy for end-to-end solutions with Azure Portal or PowerShell

Course Outline

Module 1: Operationalize end-to-end cloud analytics solutions

This module explains how to Azure Data Factory to centrally manage data from different sources.

Lessons

  • Create a data factory
  • Create a data-driven workflow
  • Monitor and manage the data factory
  • Move, Transform and Analyze Data
  • Design a deployment strategy for an end-to-end solution
  • Review

Lab: Operationalize end-to-end cloud analytics solutions

  • Create a data factory
  • Create a data-driven workflow
  • Monitor and manage the data factory
  • Move, Transform and Analyze Data
  • Design a deployment strategy for an end-to-end solution

After completing this module, students will be able to:

  • Create, Manage & Monitor a data factory
  • Create a data driven workflow
  • Move, Transform and Analyze Data
  • Create a deployment strategy using the Azure Portal or PowerShell

Module 2: Appendix B: PowerShell for Technology Professionals (Optional)

This module explains how to use PowerShell to administer computer, network, application and Azure resources.

Lessons

  • Introduction
  • Compared to Other Scripting Languages
  • Configuring and Using PowerShell
  • Creating and Running Scripts
  • Administering Local Resources
  • Administering Network Resources
  • Resolve PowerShell Scripting Problems.

Lab: Lab B: Operationalize end-to-end cloud analytics solutions

  • Use PowerShell to get Computer Information
  • Use PowerShell documentation to understand and use cmdlets
  • Create and execute scripts
  • Configure and test Remote Management
  • Create and Azure VM with Azure PowerShell

After completing this module, students will be able to use PowerShell to:

  • Use PowerShell to get Computer Information
  • Use PowerShell documentation to understand and use cmdlets
  • Create and execute scripts
  • Configure and test Remote Management
  • Create and Azure VM with Azure PowerShell

Additional Reading

To help you prepare for this class, review the following resources:

  • 55224-1A – Microsoft Azure Big Data Analytics Solutions

Prerequisites

Before attending this course, students must have:

  • Experience processing and querying bulk data
  • Experience analyzing real-time and historical data
  • Experience using SQL and data analysis / visualization tools (e.g. Power BI)
  • Experience using PowerShell (Note: A basic PowerShell tutorial is included in 55224-1.)

Additional information

Course Length

2 Days

Course Level

300

Format

Live Instructor-Led

Release Date

19-May-17

Scheduled Dates

0~2018-11-01~2018-11-02~07:10~14:00, 0~2018-11-29~2018-11-30~07:10~14:00

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