Cloud Migration Strategies | Module 5.7 | Surfalytics
Cloud migration is one of the most important skills for data engineers in 2026 — and it's a perfect project for your resume and interviews. In this lesson, we break down how to migrate on-premise analytics to the cloud, step by step. 📚 WHAT YOU'LL LEARN Theory: - Why cloud migration is still relevant for enterprises in 2026 - Two core migration strategies: Lift and Shift vs Split and Flip - Real-world migration example from Amazon (Oracle → AWS Redshift) - Key cloud migration statistics (cost, efficiency, security) - AWS Data Migration Service (DMS) and Schema Conversion Tool Hands-on: - How to build a local analytics stack (Postgres + ETL + BI) - How to migrate your local stack to AWS, Azure, or GCP - Pet project ideas that you can use on your resume ⏱️ TIMESTAMPS 📚 THEORY SECTION 0:18 - Introduction to cloud migration and why it's still one of the hottest topics in 2026 0:39 - Why startups move to the cloud easily but enterprises struggle for years 2:54 - Motivational quote and career advice on community and salary negotiation 5:16 - Key cloud migration statistics: cost savings, efficiency, features, and security 7:16 - Overview of the cloud migration process from strategy to execution 7:39 - Two migration strategies explained: Lift and Shift vs Split and Flip 8:52 - Cloud database alternatives: DynamoDB, EC2, RDS, and Aurora 9:20 - Real-world migration story from Amazon: Oracle to Redshift, Matillion, and Tableau 11:25 - How to execute data warehouse migration step by step 🛠️ HANDS-ON EXPLANATION SECTION 13:25 - AWS Data Migration Service (DMS) and Schema Conversion Tool explained 15:55 - Hands-on exercise: build a local analytics stack and migrate it to the cloud 17:43 - Choosing cloud alternatives for database, ETL, and BI tools 📦 RESOURCES MENTIONED - AWS Data Migration Service (DMS) - AWS Schema Conversion Tool (SCT) - Amazon Redshift - Matillion ETL - Tableau - Apache Spark / EMR - Azure Database Migration Service - GCP Database Migration Guides - Open-source BI tools: Metabase, Redash, Looker Data Studio - dbt (data build tool) 🎯 KEY TAKEAWAYS ✅ Cloud migration is still a top priority for enterprises — great skill for your career ✅ Lift and Shift is quick but limited; Split and Flip gives you real cloud benefits ✅ A migration project is one of the best stories you can tell in interviews ✅ AWS DMS and Schema Conversion Tool handle the heavy lifting of data and schema migration ✅ Build a pet project: local Postgres → cloud data warehouse → ETL → BI ✅ Every cloud vendor (AWS, Azure, GCP) has their own migration tools and guides ✅ Community and mentorship can save you from costly career mistakes 🔗 Join the Surfalytics community for FREE courses, mentorship, and career support! #CloudMigration #DataEngineering #AWS #Azure #GCP #CloudComputing #DataWarehouse #ETL #Redshift #Snowflake #DataEngineer #Surfalytics #LearnDataEngineering #CloudArchitecture #DatabaseMigration