Corporate Courses

DP-203: Data Engineering on Microsoft Azure

Course Outline

In this course, the student will learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines.

Location

Online

Prerequisites

DP-900

Course Content

  • Module 1: Explore compute and storage options for data engineering workloads
  • Module 2: Design and implement the serving layer
  • Module 3: Data engineering considerations for source files
  • Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools
  • Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark
  • Module 6: Data exploration and transformation in Azure Databricks
  • Module 7: Ingest and load data into the data warehouse
  • Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines
  • Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines
  • Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse
  • Module 11: Analyze and Optimize Data Warehouse Storage
  • Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
  • Module 13: End-to-end security with Azure Synapse Analytics
  • Module 14: Real-time Stream Processing with Stream Analytics
  • Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks
  • Module 16: Build reports using Power BI integration with Azure Synpase Analytics
  • Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics

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