diff --git a/website/docs/best-practices/how-we-mesh/mesh-1-intro.md b/website/docs/best-practices/how-we-mesh/mesh-1-intro.md index fcd379de9cf..819a9e04111 100644 --- a/website/docs/best-practices/how-we-mesh/mesh-1-intro.md +++ b/website/docs/best-practices/how-we-mesh/mesh-1-intro.md @@ -6,19 +6,21 @@ hoverSnippet: Learn how to get started with dbt Mesh ## What is dbt Mesh? -Organizations of all sizes rely upon dbt to manage their data transformations, from small startups to large enterprises. At scale, it can be challenging to coordinate all the organizational and technical requirements demanded by your stakeholders within the scope of a single dbt project. To date, there also hasn't been a first-class way to effectively manage the dependencies, governance, and workflows between multiple dbt projects. +Organizations of all sizes rely upon dbt to manage their data transformations, from small startups to large enterprises. At scale, it can be challenging to coordinate all the organizational and technical requirements demanded by your stakeholders within the scope of a single dbt project. -Regardless of your organization's size and complexity, dbt should empower data teams to work independently and collaboratively; sharing data, code, and best practices without sacrificing security or autonomy. dbt Mesh provides the tooling for teams to finally achieve this. +To date, there also hasn't been a first-class way to effectively manage the dependencies, governance, and workflows between multiple dbt projects. -dbt Mesh is not a single product: it is a pattern enabled by a convergence of several features in dbt: +That's where **dbt Mesh** comes in - empowering data teams to work *independently and collaboratively*; sharing data, code, and best practices without sacrificing security or autonomy. + +This guide will walk you through the concepts and implementation details needed to get started. dbt Mesh is not a single product - it is a pattern enabled by a convergence of several features in dbt: - **[Cross-project references](/docs/collaborate/govern/project-dependencies#how-to-write-cross-project-ref)** - this is the foundational feature that enables the multi-project deployments. `{{ ref() }}`s now work across dbt Cloud projects on Enterprise plans. - **[dbt Explorer](/docs/collaborate/explore-projects)** - dbt Cloud's metadata-powered documentation platform, complete with full, cross-project lineage. -- **Governance** - dbt's new governance features allow you to manage access to your dbt models both within and across projects. - - **[Groups](/docs/collaborate/govern/model-access#groups)** - groups allow you to assign models to subsets within a project. +- **Governance** - dbt's governance features allow you to manage access to your dbt models both within and across projects. + - **[Groups](/docs/collaborate/govern/model-access#groups)** - With groups, you can organize nodes in your dbt DAG that share a logical connection (for example, by functional area) and assign an owner to the entire group. - **[Access](/docs/collaborate/govern/model-access#access-modifiers)** - access configs allow you to control who can reference models. -- **[Model Versions](/docs/collaborate/govern/model-versions)** - when coordinating across projects and teams, we recommend treating your data models as stable APIs. Model versioning is the mechanism to allow graceful adoption and deprecation of models as they evolve. -- **[Model Contracts](/docs/collaborate/govern/model-contracts)** - data contracts set explicit expectations on the shape of the data to ensure data changes upstream of dbt or within a project's logic don't break downstream consumers' data products. + - **[Model Versions](/docs/collaborate/govern/model-versions)** - when coordinating across projects and teams, we recommend treating your data models as stable APIs. Model versioning is the mechanism to allow graceful adoption and deprecation of models as they evolve. + - **[Model Contracts](/docs/collaborate/govern/model-contracts)** - data contracts set explicit expectations on the shape of the data to ensure data changes upstream of dbt or within a project's logic don't break downstream consumers' data products. ## Who is dbt Mesh for? diff --git a/website/docs/best-practices/how-we-mesh/mesh-3-implementation.md b/website/docs/best-practices/how-we-mesh/mesh-3-implementation.md index 65ed5d7935b..5934c1625a3 100644 --- a/website/docs/best-practices/how-we-mesh/mesh-3-implementation.md +++ b/website/docs/best-practices/how-we-mesh/mesh-3-implementation.md @@ -127,4 +127,4 @@ We've provided a set of example projects you can use to explore the topics cover ### dbt-meshify -We recommend using the `dbt-meshify` [command line tool]() to help you do this. This comes with CLI operations to automate most of the above steps. +We recommend using the `dbt-meshify` [command line tool]() to help you do this. This comes with CLI operations to automate most of the above steps. diff --git a/website/docs/docs/collaborate/govern/model-contracts.md b/website/docs/docs/collaborate/govern/model-contracts.md index e3ea1e8c70c..09389036513 100644 --- a/website/docs/docs/collaborate/govern/model-contracts.md +++ b/website/docs/docs/collaborate/govern/model-contracts.md @@ -28,10 +28,18 @@ While this is ideal for quick and iterative development, for some models, consta ## Where are contracts supported? At present, model contracts are supported for: -- SQL models. Contracts are not yet supported for Python models. -- Models materialized as `table`, `view`, and `incremental` (with `on_schema_change: append_new_columns`). Views offer limited support for column names and data types, but not `constraints`. Contracts are not supported for `ephemeral`-materialized models. +- SQL models. +- Models materialized as one of the following: + - `table` + - `view` — Views offer limited support for column names and data types, but not `constraints`. + - `incremental` — with `on_schema_change: append_new_columns` or `on_schema_change: fail`. - Certain data platforms, but the supported and enforced `constraints` vary by platform. +Model contracts are _not_ supported for: +- Python models. +- `ephemeral`-materialized SQL models. + + ## How to define a contract Let's say you have a model with a query like: