Preferred method of contact:

Performing Big Data Engineering on Microsoft Cloud Services (20776A)

COURSE TYPE

Intermediate

Course Number

8492

Duration

5 Days

PDF Add to WishList

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.

You Will Learn How 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

Important Course Information

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

Course Outline

  • Module 1: Architectures for Big Data Engineering with Azure

This module describes common architectures for processing big data using Azure tools and services.

Lessons

  • Understanding Big Data
  • Architectures for Processing Big Data
  • Considerations for designing Big Data solutions

Lab: Designing a Big Data Architecture

  • Design a big data architecture

After completing this module, students will be able to:

  • Explain the concept of Big Data
  • Describe the Lambda and Kappa architectures
  • Describe design considerations for building Big Data Solutions with Azure
  • Module 2: Processing Event Streams using Azure Stream Analytics

This module describes how to use Azure Stream Analytics to design and implement stream processing over large-scale data.

Lessons

  • Introduction to Azure Stream Analytics
  • Configuring Azure Stream Analytics jobs

Lab: Processing Event Streams with Azure Stream Analytics

  • Create an Azure Stream Analytics job
  • Create another Azure Stream job
  • Add an Input
  • Edit the ASA job
  • Determine the nearest Patrol Car

After completing this module, students will be able to:

  • Describe the purpose and structure of Azure Stream Analytics
  • Configure Azure Stream Analytics jobs for scalability, reliability and security
  • Module 3: Performing custom processing in Azure Stream Analytics

This module describes how to include custom functions and incorporate machine learning activities into an Azure Stream Analytics job.

Lessons

  • Implementing Custom Functions

  • Incorporating Machine Learning into an Azure Stream Analytics Job

Lab: Performing Custom Processing with Azure Stream Analytics

  • Add logic to the analytics
  • Detect consistent anomalies
  • Determine consistencies using machine learning and ASA

After completing this module, students will be able to:

  • Describe how to create and use custom functions in Azure Stream Analytics
  • Describe how to use Azure Machine Learning models in an Azure Stream Analytics job
  • Module 4: Managing Big Data in Azure Data Lake Store

This module describes how to use Azure Data Lake Store as a large-scale repository of data files.

Lessons

  • Using Azure Data Lake Store
  • Monitoring and protecting data in Azure Data Lake Store

Lab: Managing Big Data in Azure Data Lake Store

  • Update the ASA Job
  • Upload details to ADLS

After completing this module, students will be able to:

  • Describe how to create an Azure Data Lake Store, create folders, and upload data
  • Explain how to monitor an Azure Data Lake account, and protect the data that it contains
  • Module 5: Processing Big Data using Azure Data Lake Analytics

This module describes how to use Azure Data Lake Analytics to examine and process data held in Azure Data Lake Store.

Lessons

  • Introduction to Azure Data Lake Analytics
  • Analyzing Data with U-SQL
  • Sorting, grouping, and joining data

Lab: Processing Big Data using Azure Data Lake Analytics

  • Add functionality
  • Query against Database
  • Calculate average speed

After completing this module, students will be able to:

  • Describe the purpose of Azure Data Lake Analytics, and how to create and run jobs
  • Describe how to use USQL to process and analyse data
  • Describe how to use windowing to sort data and perform aggregated operations, and how to join data from multiple sources
  • Module 6: Implementing custom operations and monitoring performance in Azure Data Lake Analytics

This module describes how to create and deploy custom functions and operations, integrate with Python and R, and protect and optimize jobs.

Lessons

  • Incorporating custom functionality into Analytics jobs
  • Managing and Optimizing jobs

Lab: Implementing custom operations and monitoring performance in Azure Data Lake Analytics

  • Custom extractor
  • Custom processor
  • Integration with R/Python
  • Monitor and optimize a job

After completing this module, students will be able to:

  • Describe how to incorporate custom features and assemblies into USQL
  • Describe how to implement security to protect jobs, and how to monitor and optimize jobs to ensure efficient operations
  • Module 7: Implementing Azure SQL Data Warehouse

This module describes how to use Azure SQL Data Warehouse to create a repository that can support large-scale analytical processing over data at rest.

Lessons

  • Introduction to Azure SQL Data Warehouse
  • Designing tables for efficient queries
  • Importing Data into Azure SQL Data Warehouse

Lab: Implementing Azure SQL Data Warehouse

  • Create a new data warehouse
  • Design and create tables and indexes
  • Import data into the warehouse

After completing this module, students will be able to:

  • Describe the purpose and structure of Azure SQL Data Warehouse
  • Describe how to design table to optimize the processing performed by the data warehouse
  • Describe tools and techniques for importing data into a warehouse at scale
  • Module 8: Performing Analytics with Azure SQL Data Warehouse

This module describes how to import data in Azure SQL Data Warehouse, and how to protect this data.

Lessons

  • Querying Data in Azure SQL Data Warehouse
  • Maintaining Performance
  • Protecting Data in Azure SQL Data Warehouse

Lab: Performing Analytics with Azure SQL Data Warehouse

  • Performing queries and tuning performance
  • Integrating with Power BI and Azure Machine Learning
  • Configuring security and analysing threats

After completing this module, students will be able to:

  • Describe how to perform queries and use the data held in a data warehouse to perform analytics and generate reports
  • Describe how to configure and monitor a data warehouse to maintain good performance
  • Describe how to protect data and manage security in a data warehouse
  • Module 9: Automating the Data Flow with Azure Data Factory

This module describes how to use Azure Data Factory to import, transform, and transfer data between repositories and services.

Lessons

  • Introduction to Azure Data Factory
  • Transferring Data
  • Transforming Data
  • Monitoring Performance and Protecting Data

Lab: Automating the Data Flow with Azure Data Factory

  • Automate the Data Flow with Azure Data Factory

After completing this module, students will be able to:

  • Describe the purpose of Azure Data Factory, and explain how it works
  • Describe how to create Azure Data Factory pipelines that can transfer data efficiently
  • Describe how to perform transformations using an Azure Data Factory pipeline
  • Describe how to monitor Azure Data Factory pipelines, and how to protect the data flowing through these pipelines
Show complete outline
Show Less

Convenient Ways to Attend This Instructor-Led Course

Hassle-Free Enrollment: No advance payment required to reserve your seat.
Tuition due 30 days after you attend your course.

In the Classroom

Live, Online

?
With a blend of video, text, hands-on labs, and knowledge checks, you will receive the same high quality content as the live event, but you can attend on your own time, at your own pace.

On Demand +
Instructor Coaching

Private Team Training

In the Classroom — OR — Live, Online

Tuition — Standard: $3190   Government: $2833

Oct 15 - 19 (5 Days)
9:00 AM - 4:30 PM EDT
Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

Nov 5 - 9 (5 Days)
9:00 AM - 4:30 PM EST
New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

Dec 17 - 21 (5 Days)
9:00 AM - 4:30 PM EST
Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

Jan 7 - 11 (5 Days)
9:00 AM - 4:30 PM EST
Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

Feb 4 - 8 (5 Days)
9:00 AM - 4:30 PM EST
New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

Mar 25 - 29 (5 Days)
9:00 AM - 4:30 PM EDT
Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

Apr 8 - 12 (5 Days)
9:00 AM - 4:30 PM EDT
Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

May 13 - 17 (5 Days)
9:00 AM - 4:30 PM EDT
New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

Jun 24 - 28 (5 Days)
9:00 AM - 4:30 PM EDT
Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

Jul 22 - 26 (5 Days)
9:00 AM - 4:30 PM EDT
Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Reserve Your Seat

Aug 12 - 16 (5 Days)
9:00 AM - 4:30 PM EDT
New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

Show all dates
Show fewer dates

Guaranteed to Run

When you see the "Guaranteed to Run" icon next to a course event, you can rest assured that your course event — date, time, location — will run. Guaranteed.

On Demand + Instructor Coaching
Tuition — $895

With a blend of video, text, hands-on labs, and knowledge checks, you will receive the same high quality content as the live event, but you can attend on your own time, at your own pace.

PLUS, we include access to a Microsoft Certified Trainer (MCT) to help you prepare for your certification exam and help you apply your new skills immediately… Learning Tree knows how to bring learning to life!

  • Flexibility to take the course on your own time, at your own pace
  • Forever access to the digital course materials – for any refreshers
  • You will receive a code with your purchase. The code may be redeemed for online access to this On Demand course for up to six months
  • Upon course activation, the MOC On Demand videos and labs are available for three months
  • 2 FREE hours of individual coaching from an MCT Learning Tree Instructor
  • This delivery is also eligible for Microsoft Assurance Training Vouchers (SATVs)
  • NOTE: Only live, in-class training is eligible for NASBA CPEs; on-demand training is not eligible for CPE credit

For enrolling multiple subscribers at the same time, contact us »

Private Team Training

Enrolling at least 3 people in this course? Consider bringing this (or any course that can be custom designed) to your preferred location as a private team training.

For details, call 1-888-843-8733 or Click Here »

This event has been added to your cart.

Tuition

Standard

Government

In Classroom or
Online

Standard

$3190

Government

$2833

On Demand

$895*

Private Team Training

Contact Us »

*prices exclude applicable taxes


Course Tuition Includes:

After-Course Instructor Coaching
When you return to work, you are entitled to schedule a free coaching session with your instructor for help and guidance as you apply your new skills.

Prev
Next

Training Hours

Standard Course Hours: 9:00 am – 4:30 pm
*Informal discussion with instructor about your projects or areas of special interest: 4:30 pm – 5:30 pm

Enhance Your Credentials with Professional Certification

Learning Tree's comprehensive training and exam preparation guarantees that you will gain the knowledge and confidence to achieve professional certification and advance your career.

Earn 29 Credits from NASBA

This course qualifies for 29 CPE credits from the National Association of State Boards of Accountancy CPE program. NOTE: Only live, in-class attendance qualifies for NASBA CPEs. Read more ...

- ,

Prev
Next
Chat Now

Please Choose a Language

Canada - English

Canada - Français