02/14/2022 - 02/18/2022
10:00 AM - 06:00 PM
Online Virtual Class
USD $2,895.00
Enroll
02/28/2022 - 03/04/2022
10:00 AM - 06:00 PM
Online Virtual Class
USD $2,895.00
Enroll
03/07/2022 - 03/11/2022
10:00 AM - 06:00 PM
Online Virtual Class
USD $2,895.00
Enroll

Objectives

After completing this course, students will be able to:

  • Describe common architectures for processing big data using Azure tools and services.
  • Describe how to use Azure Stream Analytics to design and implement stream processing over large-scale data.
  • Describe how to include custom functions and incorporate machine learning activities into an Azure Stream Analytics job.
  • Describe how to use Azure Data Lake Store as a large-scale repository of data files.
  • Describe how to use Azure Data Lake Analytics to examine and process data held in Azure Data Lake Store.
  • Describe how to create and deploy custom functions and operations, integrate with Python and R, and protect and optimize jobs.
  • Describe how to use Azure SQL Data Warehouse to create a repository that can support large-scale analytical processing over data at rest.
  • Describe how to use Azure SQL Data Warehouse to perform analytical processing, how to maintain performance, and how to protect the data.
  • Describe how to use Azure Data Factory to import, transform, and transfer data between repositories and services.

Audience

The primary audience for this course is data engineers (IT professionals, developers, and information workers) who plan to implement big data engineering workflows on Azure.

Prerequisites

In addition to their professional experience, students who attend this training should already have the following technical knowledge:

  • A good understanding of Azure data services.
  • A basic knowledge of the Microsoft Windows operating system and its core functionality.
  • A good knowledge of relational databases.

Duration

Five days

Outline for Operationalize Cloud Analytics Solutions with Microsoft Azure

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