any location MOC Class 20776 SQL Server Training - Dynamics Edge

any location Microsoft 20776 SQL Server Training -> Performing Big Data Engineering on Microsoft Cloud Services

Dynamics Edge4.67 4.67 out of 50 stars, based on 80 reviews.*

DynamicsEdge offers a variety of dates to choose from for Dynamics Edge Microsoft 20776 high quality SQL Server training class you can trust for the best results. Customized training may also be possible.

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

After completing this course, students will be able to:

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

Lab : Designing 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

Lab : Processing Event Streams with Azure Stream Analytics

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

Lab : Performing Custom Processing with Azure Stream Analytics

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

Lab : Managing Big Data in Azure Data Lake Store

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

Lab : Processing Big Data using Azure Data Lake Analytic

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

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

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

Lab : Implementing Azure SQL Data 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

Lab : Performing Analytics with Azure SQL 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

Lab : Automating the Data Flow with Azure Data Factory

Prerequisites

This course requires that you meet the following prerequisites:

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