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M20776 Engineering Data with Microsoft Cloud Services

Course Details

NameM20776 Engineering Data with Microsoft Cloud Services
Description
URL
Location:
Virtual Classroom
Start Date:
Working Days:
Price:
£850.00 +vat
was £1049.00
Availability:
Exam:
Residential:
Course ID:
427392
Offer

Overview

Special Notices

Please note: for Attend from Anywhere customers an additional screen is required. The additional screen must have a minimum screen size of 19 inch and minimum resolution of 1280x1024, with the vertical resolution (1024) being the most critical.

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.

Audience profile

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.

Learning 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.

Pre-Requisites

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 Content

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

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

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

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

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

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

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.

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

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

Attend From Anywhere

Description:

How Attend from Anywhere works

Our ‘Attend from Anywhere’ courses allow you to access award-winning classroom training without leaving your home or office. We use WebEx web and video conferencing platform by Cisco. Before you book you should check to ensure you meet the WebEx system requirements and run a test meeting to ensure the software is compatible with your firewall settings (if it doesn’t work you should adjust your settings or contact your IT department about permitting the website).

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  • Up to three weeks before the start of the course we will send you Joining Instructions by email.
  • You should enter ‘My Virtual Account’ to update your address for courseware and book a pre-test with a member of the Virtual Learning Team, who will check everything works.
  • 15 minutes before the course begins you should launch the software, connect your audio and familiarise yourself with the interface and how the virtual interactions work.
  • The course will be split into multiple sessions, with short breaks in between so you can stay focused and refreshed.
  • Throughout the course the learning professional will use an electronic whiteboard, which will transmit all the notes directly to your screen.
  • You can ask the learning professional a question at any time, either by simply speaking aloud through your microphone or by clicking the virtual ‘raise-a-hand’ button on the interface.
  • Towards the end of the course there will be plenty of time for detailed Q&As with the learning professional, just as if you were physically in the classroom.
  • Following the course you will be asked to complete a course evaluation form, which will allow you to give detailed feedback on your experience and help us to make future improvements.
  • For four weeks after the course has finished you will have on-demand access to helpful videos on the subject matter, and we may send you useful emails reminding you of the ‘Key Learning Points’.

Benefits of Attend from Anywhere

Access to experts

Receive full support from our subject-matter experts for the duration of your course.

Convenient

Access your training from home, the office, or anywhere with internet access.

Cost-effective

Save money on training and expenses like transport, hotels, meals and childcare.

Quality

Our technology makes our online courses the same high quality as our classroom training.

Time-efficient

Reduce time out of the office and time spent travelling to and from training centres.

FAQ

What equipment do I need for an Attend from Anywhere course?

You will need an internet-connected computer and a USB headset with an in-built mic to interact with the trainer. Two monitors are recommended; one to stream the video from the classroom and the other to display the interactive interface.

How reliable are Attend from Anywhere courses?

We use leading Cisco technology and our classrooms are specifically optimised to improve sound quality for remote attendees. We also offer a pre-test so you can test everything is working before the course starts.

How are remote attendees made to fell included?

Our trainers are specially trained on how to interact with remote attendees and our technology allows them to take over remote PCs. Our remote labs ensure all participants can take part in hands-on class exercises wherever they are.

What makes Attend from Anywhere courses cost effective?

Our technology makes our Attend from Anywhere courses the same high-quality experience as our classroom training, so we do not price them differently. However, organisations and individuals do make significant financial savings by booking this type of course when associated costs (such as travel, expenses, hotels, food and childcare) are factored in.

How can I take the exam remotely?

You may be able to take your exam via one of our accredited remote live proctors. Where this is not possible you may be issued with an exam voucher or required to attend a classroom in order to take the exam. Please contact us for specific details in relation to your course.

If you are able to take your exam remotely you need to book it before the course begins  and switch on a webcam to enable invigilation and show photo ID (please note that exam slots are subject to availability with the live proctors and may not be available during the week of the exam. Exam slots are booked on a first come first served basis).

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