Silver tables are created by applying business logic and aggregations to bronze tables, making them suitable for business reporting. Gold tables are created by further cleaning and enriching silver tables, making them suitable for ad-hoc analytics. Both batch and real-time workloads typically use silver tables as sources, while gold tables are rarely used as sources.

Silver tables are optimized for machine learning and are created by aggregating data from bronze tables. Gold tables are optimized for analytics and reporting and are created by further enriching silver tables. Real-time streaming workloads typically use bronze tables as sources, while batch reporting workloads use gold tables as sources.

Silver tables are derived from bronze tables and contain raw, unprocessed data for data science experimentation. Gold tables are derived from silver tables and contain cleaned, enriched, and aggregated data for operational reporting. Batch ETL jobs typically use gold tables as sources, while real-time analytics workloads use bronze tables as sources.

Silver tables are created by cleaning and enriching data from bronze tables and are typically used as sources for ad-hoc analytics and data exploration. Gold tables are created by aggregating and applying business logic to silver tables, and are typically used as sources for business intelligence dashboards and machine learning models. Batch ETL jobs often use bronze tables as sources, while both batch and real-time analytics workloads use gold tables as sources.