Databricks

1. Lakehouse Architecture

   Lakehouse concept, unified data and AI platform, architecture principles and workspace overview.

2. Medallion Architecture

   Bronze, silver and gold layers and incremental data quality.

3. Delta Lake

   ACID transactions, transaction log, time travel, schema enforcement and evolution, MERGE and table features.

4. Delta Optimization: OPTIMIZE, Z-order, Liquid Clustering

   File compaction, Z-ordering, liquid clustering, VACUUM, data skipping and small files.

5. Unity Catalog

   Metastore, catalogs, schemas, tables, volumes, privileges, lineage and governance.

6. Compute and Clusters

   All-purpose and job clusters, serverless compute, autoscaling, policies and runtime versions.

7. SQL Warehouses

   Serverless, pro and classic SQL warehouses, sizing, scaling and Databricks SQL.

8. Photon and Performance Optimization

   Photon engine, adaptive query execution, skew handling and query tuning.

9. Disk Cache and Caching

   Delta disk cache, Spark cache, query result cache and when each helps.

10. Jobs and Workflows

    Tasks, schedules, triggers, task dependencies, retries and orchestration with Lakeflow Jobs.

11. Data Ingestion and Auto Loader

    Auto Loader, COPY INTO, incremental file ingestion and connectors.

12. Lakeflow Declarative Pipelines

    Declarative ETL, streaming tables, materialized views and data quality expectations.

13. Structured Streaming

    Streaming reads and writes, triggers, checkpoints, watermarks and stateful processing.

14. Delta Sharing

    Open protocol for sharing data across organizations and platforms.

15. MLflow and Machine Learning

    Experiment tracking, model registry, model serving and the ML lifecycle.

Each section links to the official page. Titles and summaries by Extra Credit; the docs belong to their authors.