Microsoft Data & Power BI
Data Engineering on Microsoft Azure (DP-203/DP-203T00)
Engineer data solutions on Azure.
4 daysIntermediate34 modulesDP-203/DP-203T00Microsoft Certified: Azure Data Engineer
About this course
Engineer data solutions on Azure. Over four days you will work with Data Lake Storage Gen2, query and transform data with Synapse serverless SQL pools, analyse it with Apache Spark and Delta Lake, build Synapse pipelines, and secure data and manage users.
Curriculum
34 modules
- What is data engineering
- Important data engineering concepts
- Data engineering in Microsoft Azure
- Understand Azure Data Lake Storage Gen2
- Enable Azure Data Lake Storage Gen2 in Azure Storage
- Compare Azure Data Lake Store to Azure Blob storage
- Understand the stages for processing big data
- Use Azure Data Lake Storage Gen2 in data analytics workloads
- What is Azure Synapse Analytics
- How Azure Synapse Analytics works
- When to use Azure Synapse Analytics
- Understand Azure Synapse serverless SQL pool capabilities and use cases
- Query files using a serverless SQL pool
- Create external database objects
- Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement
- Encapsulate data transformations in a stored procedure
- Include a data transformation stored procedure in a pipeline
- Understand lake database concepts
- Explore database templates
- Create a lake database
- Use a lake database
- Choose an authentication method in Azure Synapse serverless SQL pools
- Manage users in Azure Synapse serverless SQL pools
- Manage user permissions in Azure Synapse serverless SQL pools
- Get to know Apache Spark
- Use Spark in Azure Synapse Analytics
- Analyze data with Spark
- Visualize data with Spark
- Modify and save dataframes
- Partition data files
- Transform data with SQL
- Understand Delta Lake
- Create Delta Lake tables
- Create catalog tables
- Use Delta Lake with streaming data
- Use Delta Lake in a SQL pool
- Understand pipelines in Azure Synapse Analytics
- Create a pipeline in Azure Synapse Studio
- Define data flows
- Run a pipeline
- Understand Synapse Notebooks and Pipelines
- Use a Synapse notebook activity in a pipeline
- Use parameters in a notebook
- What is Azure Synapse Analytics
- How Azure Synapse Analytics works
- When to use Azure Synapse Analytics
- Understand Azure Synapse serverless SQL pool capabilities and use cases
- Query files using a serverless SQL pool
- Create external database objects
- Get to know Apache Spark
- Use Spark in Azure Synapse Analytics
- Analyze data with Spark
- Visualize data with Spark
- Understand Delta Lake
- Create Delta Lake tables
- Create catalog tables
- Use Delta Lake with streaming data
- Use Delta Lake in a SQL pool
- Design a data warehouse schema
- Create data warehouse tables
- Load data warehouse tables
- Query a data warehouse
- Understand pipelines in Azure Synapse Analytics
- Create a pipeline in Azure Synapse Studio
- Define data flows
- Run a pipeline
- Design a data warehouse schema
- Create data warehouse tables
- Load data warehouse tables
- Query a data warehouse
- Load staging tables
- Load dimension tables
- Load time dimension tables
- Load slowly changing dimensions
- Load fact tables
- Perform post load optimization
- Scale compute resources in Azure Synapse Analytics
- Pause compute in Azure Synapse Analytics
- Manage workloads in Azure Synapse Analytics
- Use Azure Advisor to review recommendations
- Use dynamic management views to identify and troubleshoot query performance
- Understand network security options for Azure Synapse Analytics
- Configure Conditional Access
- Configure authentication
- Manage authorization through column and row level security
- Manage sensitive data with Dynamic Data Masking
- Implement encryption in Azure Synapse Analytics
- Understand hybrid transactional and analytical processing patterns
- Describe Azure Synapse Link
- 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
- What is Azure Synapse Link for SQL?
- Configure Azure Synapse Link for Azure SQL Database
- Configure Azure Synapse Link for SQL Server 2022
- Understand data streams
- Understand event processing
- Understand window functions
- Stream ingestion scenarios
- Configure inputs and outputs
- Define a query to select, filter, and aggregate data
- Run a job to ingest data
- Use a Power BI output in Azure Stream Analytics
- Create a query for real-time visualization
- Create real-time data visualizations in Power BI
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
- Data governance using Unity Catalog and Microsoft Purview
- Ingest data with Azure Databricks
- Data exploration tools in Azure Databricks
- Data analysis using DataFrame APIs
- Get to know Spark
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
- Get started with Delta Lake
- Manage ACID transactions
- Implement schema enforcement
- Data versioning and time travel in Delta Lake
- Data integrity with Delta Lake
- Explore Delta Live Tables
- Data ingestion and integration
- Real-time processing
- What are Azure Databricks Workflows?
- Understand key components of Azure Databricks Workflows
- Explore the benefits of Azure Databricks Workflows
- Deploy workloads using Azure Databricks Workflows
Who it's for
Data engineers building analytics on Azure.
Before you start
- Understanding of cloud computing and core data concepts
- Experience working with data solutions
- Recommended: AZ-900T00 Microsoft Azure Fundamentals and/or DP-900T00 Microsoft Azure Data Fundamentals
Prepares for
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