Azure Training Overview
This Microsoft official DP-203 course, Data Engineering on Microsoft Azure, teaches attendees the patterns and practices of real-time analytical solutions using Azure. Participants learn how to interactively explore data stored in files in a data lake, transform data, monitor and analyze the performance of analytical systems, and much more. This course prepares students for the DP-203 exam for which every attendee receives a voucher.
Location and Pricing
This course is taught as a private course in-person or online for teams of 3 or more. To receive a quote for online corporate training, please contact us.
In addition, some courses are available as live, instructor-led training from one of our partners.
Objectives
- Explore Azure Synapse Analytics
- Describe key concepts of an Azure Databricks solution
- Create an Azure Storage Account by using the portal
- Get started with Azure Stream Analytics
- Query files using a serverless SQL pool
- Analyze data in a lake database
- Set up security when using Azure Synapse serverless SQL pools
- Use Spark in Azure Databricks
- Use Delta Lake in Azure Databricks
- Analyze data with Spark
- Integrate SQL and Apache Spark pools in Azure Synapse Analytics
- Implement workload management
- Ingest data between various data stores using Azure Data Factory
- Examine Azure Data Factory and the core components that enable large-scale data ingestion solutions in the cloud
- Perform common data transformation and cleansing activities within Azure Data Factory without using code
- Integrate a Notebook within Azure Synapse Pipelines
- Understand how hybrid transactional/analytical processing (HTAP) can perform operational analytics with Azure Synapse Analytics
- Configure an Azure Cosmos DB Account to use Azure Synapse Link
- Approach and implement security to protect your data with Azure Synapse Analytics
- Store secrets in Azure Key Vault
- Enable Microsoft Defender for SQL and Data Classification
- Connect sending and receiving applications with Event Hubs to handle extremely high loads without losing data
Prerequisites
All students must have knowledge of cloud computing, core data concepts, and professional experience with data solutions. Attendees should have taken AZ-900: Azure Fundamentals and DP-900: Microsoft Azure Data Fundamentals, or have equivalent experience.
Outline
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Introduction to Azure Synapse Analytics
- What is Azure Synapse Analytics
- How Azure Synapse Analytics works
- When to use Azure Synapse Analytics
- Explore Azure Synapse Analytics
Explore Azure Databricks
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
- Explore Azure Databricks
Introduction to Azure Data Lake Storage
- Understand Azure Data Lake Storage Gen
- Create an Azure Storage Account by using the portal
- Compare Azure Data Lake Store to Azure Blob storage
- Understand the stages for processing big data by using Azure Data Lake Store
- Examine uses for Azure Data Lake Storage Gen
Get started with Azure Stream Analytics
- Understand data streams
- Understand event processing
- Explore Azure Stream Analytics
Use Azure Synapse Serverless SQL Pool to Query Files in a Data Lake
- Understand Azure Synapse serverless SQL pool capabilities and use cases
- Query files using a serverless SQL pool
- Create external database objects
- Query files using a serverless SQL pool
Create a Lake Database in Azure Synapse Analytics
- Understand lake database concepts
- Explore database templates
- Create a lake database
- Use a lake database
- Analyze data in a lake database
Secure Data and Manage users in Azure Synapse Serverless SQL Pools
- Choose an authentication method in Azure Synapse serverless SQL pools3 min
- Manage users in Azure Synapse serverless SQL pools3 min
- Manage user permissions in Azure Synapse serverless SQL pools
Use Apache Spark in Azure Databricks
- Get to know Spark
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
- Use Spark in Azure Databricks
Use Delta Lake in Azure Databricks
- Get Started with Delta Lake
- Create Delta Lake tables
- Create and query catalog tables
- Use Delta Lake for streaming data
- Use Delta Lake in Azure Databricks
Analyze Data with Apache Spark in Azure Synapse Analytics
- Get to know Apache Spark
- Use Spark in Azure Synapse Analytics
- Analyze data with Spark
- Visualize data with Spark
- Analyze data with Spark
Integrate SQL and Apache Spark Pools in Azure Synapse Analytics
- Describe the integration methods between SQL and spark pools in Azure Synapse Analytics
- Understand the use-cases for SQL and spark pools integration
- Authenticate in Azure Synapse Analytics
- Transfer data between SQL and spark pool in Azure Synapse Analytics
- Authenticate between spark and SQL pool in Azure Synapse Analytics
- Integrate SQL and spark pools in Azure Synapse Analytics
- Externalize the use of spark pools within Azure Synapse Workspace
- Transfer data outside the synapse workspace using the PySpark connector
Use Data Loading Best Practices in Azure Synapse Analytics
- Understand data load design goals
- Explain load methods into Azure Synapse Analytics
- Manage source data files
- Manage singleton updates
- Set up dedicated data load accounts
- Implement workload management
- Simplify ingestion with the Copy Activity
Petabyte-Scale Ingestion with Azure Data Factory or Azure Synapse Pipeline
- List the data factory ingestion methods
- Describe data factory connectors
- Use the data factory copy activity
- Manage the self-hosted integration runtime
- Set up the Azure integration runtime
Integrate Data with Azure Data Factory or Azure Synapse Pipeline
- Understand Azure Data Factory
- Describe data integration patterns
- Explain the data factory process
- Understand Azure Data Factory components
- Azure Data Factory security
- Set up Azure Data Factory
- Create linked services
- Create datasets
- Create data factory activities and pipelines
- Manage integration runtimes
Perform Code-Free Transformation at Scale with Azure Data Factory or Azure Synapse Pipeline
- Explain Azure Data Factory transformation methods
- Describe Azure Data Factory transformation types
- Author an Azure Data Factory mapping data flow
- Debug mapping data flow
- Use Azure Data Factory wrangling data
- Use compute transformations within Azure Data Factory
- Integrate SQL server integration services packages within Azure Data Factory
Orchestrate Data Movement and Transformation in Azure Data Factory or Azure Synapse Pipeline
- Understand data factory control flow
- Work with data factory pipelines
- Debug data factory pipelines
- Add parameters to data factory components
- Integrate a Notebook within Azure Synapse Pipelines
- Execute data factory packages
Plan Hybrid Transactional and Analytical Processing using Azure Synapse Analytics
- Understand hybrid transactional and analytical processing patterns
- Describe Azure Synapse Link
Implement Azure Synapse Link with Azure Cosmos DB
- Enable Cosmos DB account to use Azure Synapse Link
- Create an analytical store enabled container
- Create a linked service for Cosmos DB
- Query Cosmos DB data with Spark
- Query Cosmos DB with Synapse SQL
- Implement Azure Synapse Link for Cosmos DB
Secure a Data Warehouse in Azure Synapse Analytics
- Understand network security options for Azure Synapse Analytics
- Configure Conditional Access
- Configure authentication
- Manage authorization through column and row-level security
- Manage authorization through column and row level security
- Manage sensitive data with Dynamic Data Masking
- Implement encryption in Azure Synapse Analytics
Configure and Manage Secrets in Azure Key Vault
- Guidelines for using Azure Key Vault
- Manage access to secrets, certificates, and keys
- Store secrets in Azure Key Vault
- Manage certificates
Implement Compliance Controls for Sensitive Data
- Explore data classification
- Explore server and database audit
- Implement Dynamic Data Masking
- Implement Row Level Security
- Understand Microsoft Defender for SQL
- Explore Azure SQL Database Ledger
- Implement Azure Purview
- Enable Microsoft Defender for SQL and Data Classification
Enable Reliable Messaging for Big Data Applications using Azure Event Hubs
- Create an Event Hub using the Azure CLI
- Use the Azure CLI to Create an Event Hub
- Configure applications to send or receive messages through an Event Hub
- Configure applications to send or receive messages through an Event Hub
- Evaluate the performance of the deployed Event Hub using the Azure portal
- Evaluate the performance of the deployed Event Hub using the Azure portal
Conclusion
Training Materials
All Microsoft training students receive Microsoft official courseware.
For all Microsoft Official Courses taught in their entirety that have a corresponding certification exam, an exam
voucher is included for each participant.
Software Requirements
Attendees will not need to install any software on their computers for this class. The class will be conducted in a remote environment that Accelebrate will provide; students will only need a local computer with a web browser and a stable Internet connection. Any recent version of Microsoft Edge, Mozilla Firefox, or Google Chrome will work well.
