Master Azure for Data Engineering
Learn to design and deploy scalable data pipelines using Microsoft Azure services for modern data engineering.
This Course Includes
- 30 Hours of Hands-on Training
- Tools: Azure Data Factory, Synapse Analytics, Databricks, Event Hubs
- Online Azure Labs
- Learn ETL and Data Pipeline Skills
- Real-World Data Engineering Projects
- Serverless Data Processing with Azure Functions
Things You'll Learn
- Building scalable data pipelines with Azure Data Factory
- ETL processes with Azure Data Factory and Databricks
- Data warehousing with Azure Synapse Analytics
- Real-time data streaming with Azure Event Hubs
- Querying and analyzing data with Synapse SQL
Course Content
Introduction to Azure Data Engineering
- Overview of data engineering on Microsoft Azure.
- Key Azure services: Data Factory, Synapse Analytics, Blob Storage.
- Hands-on exercise: Setting up an Azure data engineering environment.
- Understanding data lakes vs. data warehouses in Azure.
- Introduction to Azure Free Tier for data services.
- Real-world use case: Ingesting raw data into Blob Storage.
- Navigating Azure Data Lake Storage and Synapse Studio.
- Basic Azure CLI commands for data tasks.
Data Storage and Ingestion
- Using Azure Blob Storage for scalable data storage.
- Hands-on lab: Creating Blob Storage containers for raw and processed data.
- Ingesting data with Azure Event Hubs.
- Hands-on exercise: Streaming real-time data with Event Hubs.
- Configuring Azure Data Factory for data ingestion.
- Real-world scenario: Ingesting IoT sensor data.
- Optimizing Blob Storage with lifecycle policies.
- Best practices for data partitioning and compression.
ETL with Azure Data Factory and Databricks
- Building ETL pipelines with Azure Data Factory.
- Hands-on lab: Creating a Data Factory pipeline for ETL.
- Using Azure Databricks for big data processing with Spark.
- Hands-on exercise: Transforming CSV to Parquet with Databricks.
- Integrating Data Factory with Synapse and Blob Storage.
- Real-world case study: ETL for e-commerce analytics.
- Automating Data Factory pipelines with triggers.
- Debugging and optimizing Data Factory performance.
Data Warehousing and Querying
- Setting up and managing Azure Synapse Analytics workspaces.
- Hands-on lab: Loading data into Synapse Analytics.
- Querying data with Synapse SQL.
- Hands-on exercise: Running SQL queries on Blob Storage data.
- Optimizing Synapse performance with partitioning and indexing.
- Real-world example: Building a BI dashboard with Synapse.
- Using Power BI for data visualization.
- Best practices for data warehouse design in Synapse.
Advanced Data Engineering
- Building serverless data pipelines with Azure Functions.
- Hands-on lab: Triggering Azure Functions for data processing.
- Real-time analytics with Azure Stream Analytics.
- Hands-on exercise: Analyzing streaming data with Event Hubs.
- Orchestrating pipelines with Azure Logic Apps.
- Real-world scenario: End-to-end data pipeline for marketing data.
- Monitoring pipelines with Azure Monitor.
- Preparing for Azure Data Engineer Associate certification.
Why Choose This Course?
- Led by Azure-certified data engineers
- Hands-on labs with real-world datasets
- Flexible online learning format
- Projects to showcase data engineering skills
- Prepares you for Azure Data Engineer Associate certification