Course ID: #n. a.

DP-200T01 Implementing an Azure Data Solution

Dauer: 3 Tage Daten:

In this course, 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.

1 – 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

2 – 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

3 – 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

4 – 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

5 – 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

6 – 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

7 – 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

8 – SECURING AZURE DATA PLATFORMS

  • Configuring Network Security
  • Configuring Authentication
  • Configuring Authorization
  • Auditing Security
  • Lab : Securing Azure Data Platforms

9 – 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

10 – INTEGRATING AND OPTIMIZING DATA PLATFORMS

  • Integrating data platforms
  • Optimizing data stores
  • Optimize streaming data
  • Manage disaster recovery
  • Lab : Integrating and Optimizing Data Platforms
Lernlösung

Blended Learning, Firmenseminar, Individualcoaching, Klassenraumtraining, Online Live Webinar

Sprache

Deutsch, Englisch, Französisch, Italienisch

Daten

auf Anfrage

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.

Please refer to Overview

CHF2'320 zzgl. MwSt

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