DP-203 Data Engineering on Microsoft Azure

TEMATYKA ZAJĘĆ

• Module 1: Explore compute and storage options for data engineering workloads
  Introduction to Azure Synapse Analytics
  Describe Azure Databricks
  Introduction to Azure Data Lake storage
  Describe Delta Lake architecture
  Work with data streams by using Azure Stream Analytics
  Lab: Explore compute and storage options for data engineering workloads

• Module 2: Run interactive queries using Azure Synapse Analytics serverless SQL pools
  Explore Azure Synapse serverless SQL pools capabilities
  Query data in the lake using Azure Synapse serverless SQL pools
  Create metadata objects in Azure Synapse serverless SQL pools
  Secure data and manage users in Azure Synapse serverless SQL pools
  Lab: Run interactive queries using serverless SQL pools

• Module 3: Data exploration and transformation in Azure Databricks
  Describe Azure Databricks
  Read and write data in Azure Databricks
  Work with DataFrames in Azure Databricks
  Work with DataFrames advanced methods in Azure Databricks
  Lab: Data Exploration and Transformation in Azure Databricks

• Module 4: Explore, transform, and load data into the Data Warehouse using Apache Spark
  Understand big data engineering with Apache Spark in Azure Synapse Analytics
  Ingest data with Apache Spark notebooks in Azure Synapse Analytics
  Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
  Integrate SQL and Apache Spark pools in Azure Synapse Analytics
  Lab: Explore, transform, and load data into the Data Warehouse using Apache Spark

• Module 5: Ingest and load data into the data warehouse
  Use data loading best practices in Azure Synapse Analytics
  Petabyte-scale ingestion with Azure Data Factory
  Lab: Ingest and load Data into the Data Warehouse

• Module 6: Transform data with Azure Data Factory or Azure Synapse Pipelines
  Data integration with Azure Data Factory or Azure Synapse Pipelines
  Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines
  Lab: Transform Data with Azure Data Factory or Azure Synapse Pipelines

• Module 7: Orchestrate data movement and transformation in Azure Synapse Pipelines
  Orchestrate data movement and transformation in Azure Data Factory
  Lab: Orchestrate data movement and transformation in Azure Synapse Pipelines

• Module 8: End-to-end security with Azure Synapse Analytics
  Secure a data warehouse in Azure Synapse Analytics
  Configure and manage secrets in Azure Key Vault
  Implement compliance controls for sensitive data
  Lab: End-to-end security with Azure Synapse Analytics

• Module 9: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
  Design hybrid transactional and analytical processing using Azure Synapse Analytics
  Configure Azure Synapse Link with Azure Cosmos DB
  Query Azure Cosmos DB with Apache Spark pools
  Query Azure Cosmos DB with serverless SQL pools
  Lab: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link

• Module 10: Real-time Stream Processing with Stream Analytics
  Enable reliable messaging for Big Data applications using Azure Event Hubs
  Work with data streams by using Azure Stream Analytics
  Ingest data streams with Azure Stream Analytics
  Lab: Real-time Stream Processing with Stream Analytics

• Module 11: Create a Stream Processing Solution with Event Hubs and Azure Databricks
  Process streaming data with Azure Databricks structured streaming
  Lab: Create a Stream Processing Solution with Event Hubs and Azure Databricks