Dataplex supports column-level lineage for BigQuery data

Effective AI systems operate on a foundation of context and continuous trust. When you use Dataplex Universal Catalog, Google Cloud’s unified data governance platform, the metadata that describes your data is no longer static — it’s where your AI applications can go to know where to find data and what to trust.

But when you have complex data pipelines, it’s easy for your data’s journey to become obscured, making it difficult to trace information from its origin to its eventual impact. To solve this, we are extending Dataplex lineage capabilities from object-level to column-level, starting with support for BigQuery. 

“To power our AI strategy, we need absolute trust in our data. Column-level lineage provides that. It’s the foundation for governing our data responsibly and confidently.” – Latheef Syed – AVP, Data & AI Governance Engineering at Verizon

While object-level lineage tracks the top-level connections between entire tables, column-level lineage charts the specific, granular path of a single data column as it moves and transforms. With that, we are now providing a dynamic and granular map to govern your data-to-AI ecosystem, so you can ground your agentic AI applications in context. Lineage is upgraded to Column-level at no extra cost.

Answering critical questions about your data

Data professionals often need precise answers about the complex relationships in their BigQuery datasets. Column-level lineage provides a graph of data flows that you can trace to find these answers quickly. Now you can:

• Confirm that a column used in your AI models originates from an authoritative source

• Understand how changes to one column affect other columns downstream before you make a modification

• Trace the root cause of an issue with a column by examining its upstream transformations

• Verify that sensitive data at the column level is used correctly throughout your organization

“Column-level lineage takes the trusted map of our data ecosystem to the next level. It’s the precision tool we need to fully understand the impact of a change, trace a problem to its source, and ensure compliance down to the most granular detail.” – Arvind Rajagopalan – AVP, Data / AI & Product Engineering at Verizon