Title: ETL vs ELT: What’s the Difference and Why It Matters in Data Engineering

  1. Introduction

    • Briefly explain what data pipelines are and why they matter
    • Hook: “In today’s world of Big Data, ETL and ELT are more than buzzwords.”

  2. What is ETL?

    • Extract → Transform → Load
    • Common tools: Talend, Apache Nifi, traditional systems

  3. What is ELT?

    • Extract → Load → Transform
    • Popular with cloud-native platforms (e.g., Snowflake, BigQuery)

  4. ETL vs ELT: Key Differences

    • Diagram (optional)
    • Processing power location (on-prem vs cloud)
    • Use cases and flexibility

  5. Which One Should You Use?

    • Context-based recommendation

  6. Tools Supporting ELT (Mention OLake, Apache Iceberg subtly)

  7. Final Thoughts

    • Future of ELT, growing trend of Lakehouses