Non-technical people are now generating massive amounts of data code through AI agents instead of waiting for BI teams, but this code lives everywhere—scattered across chats, laptops, and Slack—with no way to verify accuracy, reproduce results, or enforce standards. Traditional BI tools can't fix this because they're too rigid, leaving data teams stuck between chaos and lockdown.

• Millions of non-technical users are writing billions of lines of AI-generated code for analytics, replacing the old ticket-and-wait model with instant answers—and nobody wants to go back.
• The generated code is ungoverned and untraceable: there's no record of what context the AI used, which tables it queried, or what filters it dropped, making it impossible to verify if the numbers are actually correct.
• Data teams face a false choice: either let people generate whatever they want and abandon governance, or force them back into rigid BI tools that can't do much of anything.

Marquez is an open-source metadata server that collects and visualizes data lineage across your organization's pipelines. It works with major tools like Airflow, Spark, dbt, and Dagster to show you where data comes from, where it goes, and how jobs depend on each other.

• Real-time metadata collection through an OpenLineage-compatible API endpoint that integrates with existing data orchestration tools
• Web UI displays data dependencies and lineage as a visual graph, letting you trace datasets back through pipelines and see job inputs/outputs
• Lineage API enables automation for tasks like backfills and root cause analysis by letting you query dependencies across multiple platforms

Docglow replaces built-in dbt docs with an interactive single-page app that works out of the box with any compiled dbt Core project. It generates a static site featuring unlimited models, column-level lineage, project health scores, full-text search, AI-powered chat, and dark mode with zero configuration.

• Two commands (pip install + generate) turn compiled dbt artifacts into a static docs site with no dbt Cloud or backend required.
• Includes column-level lineage tracing with transformation labels (direct/derived/aggregated) and a health score for docs/test/description coverage.
• Can gate CI pipelines with --fail-under and cut large-project payloads by up to 60% by skipping column lineage or slimming output.
• AI chat and an MCP server let editors query project metadata directly, with chat streaming via a user-supplied Anthropic key rather than shipping it.