[sspaeti]

Excerpt:

    - Language: SQL and Python Continue to Dominate, With Rust Looking Promising
    - Abstraction: Custom ETL Is Replaced by Data Connectors
    - Latency: Better Tools Available In The Streaming Domain
    - Architecture: New Data Architectures Like Lakehouse and Semantic Layer Are on the Rise
    - Trust: Data Quality and Observability Become an Essential
    - Usability: The New Focus Is on Data Products and Data Contracts
    - Openness: When It Comes to Data Tools, Open Source Is the Answer
    - Standards: Database Open Standard Simplified by DuckDB
    - Roles: Data Practitioners Expand Their Knowledge into Data Engineering
    - Collaboration: DataOps Reduces Data Silos and Improves Teamwork
    - Adoption: Data Engineering Is Key Regardless of Industry or Business Size
    - Foundations: The Data Engineering Lifecycle is Evergreen