Course Code: M-DP200-G1
Duration: 3 days
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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.
After completing the course delegates will be able to:
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
Choose a data storage approach in Azure
Create an Azure Storage Account
Explain Azure Data Lake Storage
Upload data into Azure Data Lake
Explain Azure Databricks
Describe the Team Data Science Process
Provision Azure Databricks and workspaces
Perform data preparation tasks
Create an Azure Cosmos DB database built to scale
Insert and query data in your Azure Cosmos DB database
Build a .NET Core app for Azure Cosmos DB in Visual Studio Code
Distribute your data globally with Azure Cosmos DB
Explain SQL Database and SQL Data Warehouse
Provision an Azure SQL database to store application data
Provision and load data in Azure SQL Data Warehouse
Import data into Azure SQL Data Warehouse using PolyBase
Explain data streams and event processing
Querying streaming data using Stream Analytics
How to process data with Event Hubs and Stream Analytics
How to process data with Azure Blob and Stream Analytics
Explain how Azure Data Factory works
Create Linked Services and Datasets
Create Pipelines and Activities
Azure Data Factory pipeline execution and triggers
Use storage account keys
Use shared access signatures
Control network access
Understand transport-level encryption with HTTPS
Understand Advanced Threat Detection
Explain the monitoring capabilities that are available
Explain the Data Engineering troubleshooting approach
Troubleshoot common data storage issues
Troubleshoot common data processing issues
Integrate data platforms
Optimize relational data stores
Optimize NoSQL data stores
Optimize Streaming data stores
Manage disaster recovery
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.
In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses: M-AZ-900T01 Microsoft Azure Fundamentals
NOTE: Course technical content is subject to change without notice.
Implementing an Azure Data Solution
Duration: 3 days
RRP: £1,645.00 exc. VAT
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|05 Oct 2020||Spaces||Book|
|30 Nov 2020||Spaces||Book|
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|10 Aug 2020||Spaces||Book|
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