Implementing an Azure Data Solution Associate

OVERVIEW

In this course, the students will implement various data platform technologies into solutions that are in line with business and technical requirements including on-premises, cloud, and hybrid data scenarios incorporating both relational and No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.

The students will also explore how to implement data security including authentication, authorization, data policies and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing and streaming data solutions.

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure.  The secondary audience for this course is individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure.

COURSE LENGTH: 3 Days,

 

DELIVERY: Online or In-Class.

COURSE OBJECTIVES

  • Working with Data Storage

  • Enabling Team Based Data Science with Azure Databricks

  • Building Globally Distributed Databases with Cosmos DB

  • Working with Relational Data Stores in the Cloud

  • Performing Real-Time Analytics with Stream Analytics

  • Orchestrating Data Movement with Azure Data Factory

  • Securing Azure Data Platforms

  • Monitoring and Troubleshooting Data Storage and Processing

  • Integrating and Optimizing Data Platforms

CLASS PREREQUESITES

  • Azure Fundamentals - 1 day course

Course Overview

Azure for the Data Engineer

Explain the evolving world of data

Survey the services in the Azure Data Platform

Identify the tasks that are performed by a Data Engineer

Describe the use cases for the cloud in a Case Study

Lab : Azure for the Data Engineer

Identify the evolving world of data

Determine the Azure Data Platform Services

Identify tasks to be performed by a Data Engineer

Working with Data Storage

Choose a data storage approach in Azure

Create an Azure Storage Account

Explain Azure Data Lake storage

Upload data into Azure Data Lake

Lab : Working with Data Storage

Choose a data storage approach in Azure

Create a Storage Account

Explain Data Lake Storage

Upload data into Data Lake Store

Enabling Team Based Data Science with Azure Databricks

Explain Azure Databricks and Machine Learning Platforms

Describe the Team Data Science Process

Provision Azure Databricks and workspaces

Perform data preparation tasks

Lab : Enabling Team Based Data Science with Azure Databricks

Explain Azure Databricks and Machine Learning Platforms

Describe the Team Data Science Process

Provision Azure Databricks and Workspaces

Perform Data Preparation Tasks

Building Globally Distributed Databases with Cosmos DB

Create an Azure Cosmos DB database built to scale

Insert and query data in your Azure Cosmos DB database

Provision a .NET Core app for Cosmos DB in Visual Studio Code

Distribute your data globally with Azure Cosmos DB

Lab : Building Globally Distributed Databases with Cosmos DB

Create an Azure Cosmos DB

Insert and query data in Azure Cosmos DB

Build a .Net Core App for Azure Cosmos DB using VS Code

Distribute data globally with Azure Cosmos DB

Working with Relational Data Stores in the Cloud

SQL Database and SQL Data Warehouse

Provision an Azure SQL database to store data

Provision and load data into Azure SQL Data Warehouse

Lab : Working with Relational Data Stores in the Cloud

Explain SQL Database and SQL Data Warehouse

Create an Azure SQL Database to store data

Provision and load data into Azure SQL Data Warehouse

Performing Real-Time Analytics with Stream Analytics

Explain data streams and event processing

Querying streaming data using Stream Analytics

How to process data with Azure Blob and Stream Analytics

How to process data with Event Hubs and Stream Analytics

Lab : Performing Real-Time Analytics with Stream Analytics

Explain data streams and event processing

Querying streaming data using Stream Analytics

Process data with Azure Blob and Stream Analytics

Process data with Event Hubs and Stream Analytics

Orchestrating Data Movement with Azure Data Factory

Explain how Azure Data Factory works

Create Linked Services and datasets

Create pipelines and activities

Azure Data Factory pipeline execution and triggers

Lab : Orchestrating Data Movement with Azure Data Factory

Explain how Data Factory Works

Create Linked Services and Datasets

Create Pipelines and Activities

Azure Data Factory Pipeline Execution and Triggers

Securing Azure Data Platforms

Configuring Network Security

Configuring Authentication

Configuring Authorization

Auditing Security

Lab : Securing Azure Data Platforms

Configure network security

Configure Authentication

Configure Authorization

Explore SQL Server Books Online

Monitoring and Troubleshooting Data Storage and Processing

Data Engineering troubleshooting approach

Azure Monitoring Capabilities

Troubleshoot common data issues

Troubleshoot common data processing issues

Lab : Monitoring and Troubleshooting Data Storage and Processing

Explain the Data Engineering troubleshooting approach

Explain the monitoring capabilities that are available

Troubleshoot common data storage issues

Troubleshoot common data processing issues

Integrating and Optimizing Data Platforms

Integrating data platforms

Optimizing data stores

Optimize streaming data

Manage disaster recovery

Lab : Integrating and Optimizing Data Platforms

Integrate Data Platforms

Optimize Data Stores

Optimize Streaming Data

Manage Disaster recovery

You will be invoiced via Email
 

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