Performing Big Data Engineering on Microsoft Cloud Services

Course Code:
MS20776

Duration:
5 days
9.00am to 5.00pm
Location:
80 Jurong East Street 21 #04-04
Devan Nair Institute
Singapore 609607
Course Fees:
S$3,000 (excl of G.S.T)
2019 Course Dates
29 Jul  – 2 Aug 2019
30 Sep – 4 Oct 2019
11 – 15 Nov 2019
None of the published dates will work for you? Speak to our training consultants for a private tuition arrangement or a closed door training.
Do note that this course listed is a Microsoft Digital Class (DMOC Class). You are required to bring your own device.

Course Overview

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.

Course Objectives

• 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

Course Outline

Module 1: Architectures for Big Data Engineering with Azure

Module 2: Processing Event Streams using Azure Stream Analytics

Module 3: Performing custom processing in Azure Stream Analytics

Module 4: Managing Big Data in Azure Data Lake Store

Module 5: Processing Big Data using Azure Data Lake Analytics

Module 6: Implementing custom operations and monitoring performance in Azure Data Lake Analytics

Module 7: Implementing Azure SQL Data Warehouse

Module 8: Performing Analytics with Azure SQL Data Warehouse

Module 9: Automating the Data Flow with Azure Data Factory

Click Here for full course outline

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