Installation
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Woven helps Data teams federate data ownership and governance to Software engineers. With Woven, data policies can be enforced as part of Pull Requests when data models are defined and before data is created.
Woven's core capability is enabling code-synced metadata. Woven detects data model changes in Pull Requests and automatically requires that Software engineers update the data model's metadata. Woven makes suggestions that the developer can review, revise and approve.
This metadata covers the basics such as semantic description, data classification, and data access. It is also extensible to support other data policies such as replication configuration, GDPR compliance, etc.
We support a handful of schema frameworks today -- Activerecord, Sequelize, TypeORM, Prisma, PynamoDB, SqlAlchemy, dbt -- but eager to support more as needed - so, please reach out if you need us support something else.
Installing Woven is as simple as to the repo(s) where data schemas are defined. This sets up the organization to start federating data ownership to software engineers.
Woven's onboarding experience enables the organization to incrementally onboard data models, one team at a time. Once onboarded, the data models are protected by enforcing data policies as part of CI/CD - the Pull Request will be blocked when policies aren't met.
Just the GitHub app installation is sufficient to enable Code-synced metadata. Further integrations with your data stack unlocks additional capabilities
dbt requires one more thing: Woven uses the catalog.json and manifest.json files to detect dbt model changes. If you use dbt Cloud, then Woven can pull the artifacts from dbt Cloud with no additional work for you -- just follow our . If you use dbt-core, for instructions.
A popular data policy is to prevent or proactively mitigate downstream analytics/ML impact from data schema. Woven enables data teams to surface downstream Snowflake dependencies as part of Pull Request when a relevant schema is changed.
A lot of data problems could be prevented if the Data team knew about an upcoming schema change ahead of time. Woven strives to close the gap between Data producers and Data consumers & stewards through a Slack integration.
Woven enables that by sending real-time notification to Slack, when a PR with a data model change is created or merged.
Woven to pull query history and extract column level lineage. Woven will then surface impacted users and tables on every PR thereby providing awareness to software engineers. This is extensible to enforce other policies such as adding blocking reviewer when an upstream model impacts a critical dashboard.