Performing Big Data Engineering on Microsoft Cloud Services (MS-20776)

The course also explains how to include custom functions, and integrate Python and R.
  • Virtual Classroom

    Learning Style
  • Intermediate

    Difficulty
  • 5 Days

    Course Duration
  • 5 Days

    SATV Value
Upcoming Dates
When you subscribe, you get:
Master subscription plan gives you access to this course PLUS:

  • high impact technical, end user and leadership courses
  • Includes courses in multi-modality - online self-paced + Virtual Classroom courses
  • Peer to peer learning and access to expert mentors
  • Learner and Manager Analytics
  • Access to Cognitive Learning Research platform to troubleshoot project issues
On Sale!
Now Only $1,999.00 Regular Price $3,499.00
Now Only $1,999.00 Regular Price $3,499.00
/ Year
Team
Pricing
  • Buy 5-9 Enrollments And Save 5% ($1,899.00 ea.)
  • Buy 10-19 Enrollments And Save 10% ($1,799.00 ea.)
  • Buy 20-above Enrollments And Save 15% ($1,699.00 ea.)
The course also explains how to include custom functions, and integrate Python and R.

About this course:

This five-day instructor-led course describes how to process Big Data using Azure tools and services including Azure Stream Analytics, Azure Data Lake, Azure SQL Data Warehouse and Azure Data Factory. The course also explains how to include custom functions, and integrate Python and R.
The average salary for a Data Professional with Microsoft Azure skills is $111,181 per year.

Course Objective:

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.

Prerequisite:

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.

Suggested prerequisites courses:

More Information
Brand Microsoft
Lab Access Yes
Technology Microsoft
Learning Style Virtual Classroom
Difficulty Intermediate
Course Duration 5 Days
Language English
SATV Value 5 Days
VPA Eligible VPA Eligible
Write Your Own Review
Only registered users can write reviews. Please Sign in or create an account
Sales Support

Sales (866) 991-3924

Mon-Fri. 8am-6pm CST

Have Questions? Ask Us.

Why QuickStart

Turn Training Into A Personalized Learning Experience


  • Problem Solving through ExpertConnect & Peer-To-Peer Learning
  • Find The Quickest Path To Learn With Career Paths
  • Access All Courses With Master Subscription
  • Manage Your Team With Learning Analytics
  • Virtual Classroom Training & Self-Paced Learning
  • Integrate With Your LMS Through API's