Unit 1: Understanding the Cloud Data Landscape
Unit 2: Multi-Cloud Strategy & Snowflake
Unit 3: Architectural Patterns & Integration
Advanced Cloud Data Engineering for Snowflake Professionals: Azure, AWS, and Databricks Integration
Master multi-cloud data engineering by integrating Snowflake with Azure, AWS, and Databricks, designing robust pipelines, optimizing performance, and implementing comprehensive governance strategies.
Unit 1: Batch Ingestion with Azure Data Factory
Unit 2: Real-time Ingestion with Azure Streaming Services
Unit 3: Event-Driven Orchestration with Azure Functions & Logic Apps
Unit 1: Foundations of AWS Data Ingestion
Unit 2: Batch Data Ingestion with AWS Glue
Unit 3: Real-time Data Ingestion with Kinesis
Unit 4: Orchestration and Automation
Unit 1: Databricks Fundamentals & Integration
Unit 2: Advanced Data Transformations with Spark
Unit 3: Machine Learning Data Pipelines
Unit 4: Real-time Analytics with Structured Streaming
Unit 1: Cloud Storage Fundamentals for Data Engineers
Unit 2: Compute Services for Data Transformation
Unit 3: Cost & Performance Optimization
Unit 1: Foundations of Multi-Cloud Data Governance
Unit 2: Multi-Cloud Data Security Best Practices
Unit 3: Monitoring, Logging & Alerting for Data Pipelines