Coginiti + Google BigQuery
Semantic Intelligence for Google BigQuery
BigQuery delivers serverless scale with nothing to manage. Coginiti gives your team a validated, code-first workspace to discover, transform, test, and define business meaning on BigQuery, and a semantic layer that serves those definitions to Looker, other BI tools, and AI agents alike.
Coginiti is a validated Google Cloud Ready - BigQuery partner.Better Together
Google BigQuery runs the data. Coginiti runs the meaning.
BigQuery is the warehouse you never have to size. Storage and compute separate cleanly, queries scale across petabytes, and the platform keeps absorbing new workloads, from Iceberg tables in BigLake to in-warehouse machine learning.
Serverless scale has a flip side: it is easy for a growing team to scan more than it should, define metrics inconsistently across projects and datasets, and lose the context behind a query when its author moves on. The platform does not know which of your three revenue queries is the right one.
Coginiti holds that knowledge. It has earned the Google Cloud Ready - BigQuery designation, which validates that the integration meets Google's requirements for functionality and best practices. Develop and test SQL against BigQuery in the Data Workbench, promote it into versioned CoginitiScript packages, and publish governed definitions to a semantic layer that every consumer shares.
Why Coginiti and Google BigQuery Work Together
Google Cloud Ready
A validated BigQuery integration.
Coginiti carries the Google Cloud Ready - BigQuery designation. Google's engineering teams evaluated the integration against a core set of functional and interoperability requirements, so you can adopt it with confidence.
Scan Less. Spend Less.
Catch the expensive query before it runs.
Coginiti's profiling, static analysis, and explain plans surface unpartitioned scans and unbounded joins in the editor. Shared, tested logic means teams reuse a trusted query instead of paying to rediscover it.
BigLake and Iceberg
Open storage, consistent definitions.
Coginiti supports BigQuery with Apache Iceberg tables alongside native tables. Semantic definitions and transformations stay stable whether the data lives in BigQuery storage or in open formats on Cloud Storage.
Everything Coginiti Does on Google BigQuery
From the first exploratory query to the governed answer an executive reads, one platform covers the full lifecycle.
Data Discovery
Find it. Profile it. Trust it.
Browse projects, datasets, tables, and views from the Coginiti Database Explorer, profile columns in BigQuery tables on demand, and search the Analytics Catalog for the queries and models your team already trusts before writing another one.
Explore Data WorkbenchData Transformation
Modular, governed transformation in the language of SQL.
Write modular CoginitiScript transformations that compile to GoogleSQL. Parameterize by project and environment, reuse blocks across datasets, version every change, and run pipelines from the workbench or the Execution API.
Explore CoginitiScriptData Quality Testing
Encode assumptions. Validate everything.
Declare schema, uniqueness, completeness, integrity, and volume tests as CoginitiScript test blocks that run on BigQuery. Critical failures stop a pipeline before a bad load reaches Looker; monitoring failures log and continue on a schedule.
Explore CoginitiScript testingSemantic Layer
Define once. Trust everywhere.
Define entities, dimensions, measures, and relationships over BigQuery once and serve them to Looker and other BI tools over JDBC and ODBC, and to AI agents through semantic SQL. One definition, every consumer.
Explore Semantic LayerCoginiti Forge
An AI co-developer for the people who build the foundation.
Forge is the co-development agent for BigQuery practitioners. It helps define the semantic graph over your datasets, drafts CoginitiScript transformations and tests, and encodes the business context behind each asset so it persists beyond any individual.
Explore AI AgentsCoginiti Guide
Governed answers for stakeholders who need BI, not SQL.
Guide gives business stakeholders governed, plain-language answers from BigQuery data, with tables and charts computed from published definitions rather than raw tables, and without granting anyone dataset-level access they do not need.
Explore AI AgentsBuilt for Google BigQuery
Connectivity
- •Google Cloud Ready - BigQuery validated integration from the Coginiti Data Workbench
- •Authenticate with a service account JSON key, Application Default Credentials, or OAuth 2.0 user credentials
- •BigQuery native tables and BigQuery with Apache Iceberg tables both supported
- •Google Cloud SQL, AlloyDB, Google Cloud Storage, and Dataproc covered alongside BigQuery
Where It Fits
- •Google Cloud-standard organizations that want code-first governance behind Looker
- •Teams controlling BigQuery spend through shared, tested, reusable logic
- •Enterprises running BigQuery beside on-premises Oracle, Db2, or Teradata systems
- •AI initiatives that need Vertex-era agents grounded in governed BigQuery definitions
See Coginiti on Google BigQuery
Bring your own schema. We’ll walk through discovery, transformation, testing, and the semantic layer on your Google BigQuery environment.
Don't take our word for it.
Ask your favorite AI assistant to weigh in on Coginiti.