diff --git a/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md b/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md index e50542a446c..628fd7a8451 100644 --- a/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md +++ b/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-1-intro.md @@ -32,5 +32,5 @@ If you're ready to ship your users more power with less code, let's dive in! :::info MetricFlow is a new way to define metrics in dbt and one of the key components of the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl). It handles SQL query construction and defines the specification for dbt semantic models and metrics. -To fully experience the dbt Semantic Layer, including the ability to query dbt metrics via external integrations, you'll need a [dbt Cloud Team or Enterprise account](https://www.getdbt.com/pricing/). +To fully experience the dbt Semantic Layer, including the ability to query dbt metrics via external integrations, you'll need a [dbt Cloud Team or Enterprise account](https://www.getdbt.com/pricing/). Refer to [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) for more information. ::: diff --git a/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-7-conclusion.md b/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-7-conclusion.md index 1870b6b77e4..5eaa6f3ca3f 100644 --- a/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-7-conclusion.md +++ b/website/docs/best-practices/how-we-build-our-metrics/semantic-layer-7-conclusion.md @@ -32,4 +32,4 @@ pagination_next: null The dbt Semantic Layer is the biggest paradigm shift thus far in the young practice of analytics engineering. It's ready to provide value right away, but is most impactful if you move your project towards increasing normalization, and allow MetricFlow to do the denormalization for you with maximum dimensionality. -We will be releasing more resources soon covering implementation of the Semantic Layer in dbt Cloud with various integrated BI tools. This is just the beginning, hopefully this guide has given you a path forward for building your data platform in this new era. +We will be releasing more resources soon covering implementation of the Semantic Layer in dbt Cloud with various integrated BI tools. This is just the beginning, hopefully this guide has given you a path forward for building your data platform in this new era. Refer to [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) for more information. diff --git a/website/docs/docs/build/build-metrics-intro.md b/website/docs/docs/build/build-metrics-intro.md index d6b97be699b..58dca9e8f35 100644 --- a/website/docs/docs/build/build-metrics-intro.md +++ b/website/docs/docs/build/build-metrics-intro.md @@ -65,5 +65,4 @@ MetricFlow allows you to: - [The dbt Semantic Layer: what's next](https://www.getdbt.com/blog/dbt-semantic-layer-whats-next/) blog - [Get started with MetricFlow](/docs/build/sl-getting-started) - - +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) diff --git a/website/docs/docs/build/sl-getting-started.md b/website/docs/docs/build/sl-getting-started.md index 4274fccf509..78c37f201bc 100644 --- a/website/docs/docs/build/sl-getting-started.md +++ b/website/docs/docs/build/sl-getting-started.md @@ -70,19 +70,21 @@ import SlSetUp from '/snippets/_new-sl-setup.md'; -## FAQs - -If you're encountering some issues when defining your metrics or setting up the dbt Semantic Layer, check out a list of answers to some of the questions or problems you may be experiencing. - -import SlFaqs from '/snippets/_sl-faqs.md'; - - - ## Next steps +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) - [About MetricFlow](/docs/build/about-metricflow) - [Build your metrics](/docs/build/build-metrics-intro) - [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) - Demo on [how to define and query metrics with MetricFlow](https://www.loom.com/share/60a76f6034b0441788d73638808e92ac?sid=861a94ac-25eb-4fd8-a310-58e159950f5a) - [Billing](/docs/cloud/billing) + + diff --git a/website/docs/docs/dbt-cloud-apis/sl-api-overview.md b/website/docs/docs/dbt-cloud-apis/sl-api-overview.md index 0ddbc6888db..9c3bf912597 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-api-overview.md +++ b/website/docs/docs/dbt-cloud-apis/sl-api-overview.md @@ -15,7 +15,7 @@ import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; -The rapid growth of different tools in the modern data stack has helped data professionals address the diverse needs of different teams. The downside of this growth is the fragmentation of business logic across teams, tools, and workloads.
+The rapid growth of different tools in the modern data stack has helped data professionals address the diverse needs of different teams. The downside of this growth is the fragmentation of business logic across teams, tools, and workloads.

The [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) allows you to define metrics in code (with [MetricFlow](/docs/build/about-metricflow)) and dynamically generate and query datasets in downstream tools based on their dbt governed assets, such as metrics and models. Integrating with the dbt Semantic Layer will help organizations that use your product make more efficient and trustworthy decisions with their data. It also helps you to avoid duplicative coding, optimize development workflow, ensure data governance, and guarantee consistency for data consumers. diff --git a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md index 8427a15cc11..684ece52b74 100644 --- a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md +++ b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md @@ -39,3 +39,4 @@ import AvailIntegrations from '/snippets/_sl-partner-links.md'; - [dbt Semantic Layer API query syntax](/docs/dbt-cloud-apis/sl-jdbc#querying-the-api-for-metric-metadata) - [Hex dbt Semantic Layer cells](https://learn.hex.tech/docs/logic-cell-types/transform-cells/dbt-metrics-cells) to set up SQL cells in Hex. - [Resolve 'Failed APN'](/faqs/Troubleshooting/sl-alpn-error) error when connecting to the dbt Semantic Layer. +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) diff --git a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md index 8ea9d51005c..3b81e700fce 100644 --- a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md @@ -19,9 +19,9 @@ import DeprecationNotice from '/snippets/_sl-deprecation-notice.md'; The dbt Semantic Layer, powered by [MetricFlow](/docs/build/about-metricflow), simplifies the process of defining and using critical business metrics, like `revenue` in the modeling layer (your dbt project). By centralizing metric definitions, data teams can ensure consistent self-service access to these metrics in downstream data tools and applications. The dbt Semantic Layer eliminates duplicate coding by allowing data teams to define metrics on top of existing models and automatically handles data joins. -Moving metric definitions out of the BI layer and into the modeling layer allows data teams to feel confident that different business units are working from the same metric definitions, regardless of their tool of choice. If a metric definition changes in dbt, it’s refreshed everywhere it’s invoked and creates consistency across all applications. +Moving metric definitions out of the BI layer and into the modeling layer allows data teams to feel confident that different business units are working from the same metric definitions, regardless of their tool of choice. If a metric definition changes in dbt, it’s refreshed everywhere it’s invoked and creates consistency across all applications. -Refer to the [Why we need a universal semantic layer](https://www.getdbt.com/blog/universal-semantic-layer/) blog post to learn more. +Refer to the [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) or [Why we need a universal semantic layer](https://www.getdbt.com/blog/universal-semantic-layer/) blog post to learn more. ## Explore the dbt Semantic Layer diff --git a/website/docs/docs/use-dbt-semantic-layer/exports.md b/website/docs/docs/use-dbt-semantic-layer/exports.md index 8e7048cc3b3..79d94f7bebf 100644 --- a/website/docs/docs/use-dbt-semantic-layer/exports.md +++ b/website/docs/docs/use-dbt-semantic-layer/exports.md @@ -202,3 +202,6 @@ Exports provide an integration path for tools that don't natively connect with t You can use exports to create a custom integration with tools such as PowerBI, and more. + +## Related docs +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) diff --git a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md index 11a610805a9..a4ff32e8234 100644 --- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md @@ -88,17 +88,9 @@ import SlSetUp from '/snippets/_new-sl-setup.md'; - -## FAQs - -If you're encountering some issues when defining your metrics or setting up the dbt Semantic Layer, check out a list of answers to some of the questions or problems you may be experiencing. - -import SlFaqs from '/snippets/_sl-faqs.md'; - - - - ## Next steps + +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) - [Set up dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-sl) - [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) - Demo on [how to define and query metrics with MetricFlow](https://www.loom.com/share/60a76f6034b0441788d73638808e92ac?sid=861a94ac-25eb-4fd8-a310-58e159950f5a) diff --git a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md index 1016de1830a..47d6f3af302 100644 --- a/website/docs/docs/use-dbt-semantic-layer/setup-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/setup-sl.md @@ -40,12 +40,10 @@ import SlSetUp from '/snippets/_new-sl-setup.md'; 8. You’re done 🎉! The semantic layer should is now enabled for your project. --> - - ## Related docs - [Build your metrics](/docs/build/build-metrics-intro) - [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) - [Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview) -- [Migrate your legacy Semantic Layer](/guides/sl-migration) - [Get started with the dbt Semantic Layer](/docs/use-dbt-semantic-layer/quickstart-sl) +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) diff --git a/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md b/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md index 05fb06fd93d..5f0c50b3e43 100644 --- a/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md +++ b/website/docs/docs/use-dbt-semantic-layer/sl-architecture.md @@ -2,7 +2,7 @@ title: "dbt Semantic Layer architecture" id: sl-architecture description: "dbt Semantic Layer product architecture and related questions." -sidebar_label: "Architecture" +sidebar_label: "Semantic Layer architecture" tags: [Semantic Layer] pagination_next: null --- @@ -46,8 +46,5 @@ The following table compares the features available in dbt Cloud and source avai | Connect to downstream integrations (Tableau, Hex, Mode, Google Sheets, and so on.) | ❌ | ✅ | | Create and run Exports to save metrics queries as tables in your data platform. | ❌ | ✅ | -## FAQs - -import SlFaqs from '/snippets/_sl-faqs.md'; - - +## Related docs +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) diff --git a/website/docs/docs/use-dbt-semantic-layer/sl-faqs.md b/website/docs/docs/use-dbt-semantic-layer/sl-faqs.md new file mode 100644 index 00000000000..a430d13b29d --- /dev/null +++ b/website/docs/docs/use-dbt-semantic-layer/sl-faqs.md @@ -0,0 +1,258 @@ +--- +title: "dbt Semantic Layer FAQs" +id: sl-faqs +description: "Read the FAQs to learn more about the dbt Semantic Layer, how it works, how to build metrics, integrations, and more." +sidebar_label: "Semantic Layer FAQs" +tags: [Semantic Layer] +pagination_next: "docs/use-dbt-semantic-layer/avail-sl-integrations" +--- + +The [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) is a dbt Cloud offering that allows users to centrally define their metrics within their dbt project using [MetricFlow](/docs/build/about-metricflow). + +The dbt Semantic Layer offers: + +- Dynamic SQL generation to compute metrics +- APIs to query metrics and dimensions +- First-class [integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) to query those centralized metrics in downstream tools + +The dbt Semantic Layer is powered by MetricFlow, which is a source-available component. + +## Overview of the dbt Semantic Layer + + + +The primary value of the dbt Semantic Layer is to centralize and bring consistency to your metrics across your organization. Additionally, it allows you to: + +- **Meet your users where they are** by being agnostic to where your end users consume data through the supporting of different APIs for integrations. +- **Optimize costs** by spending less time preparing data for consumption. +- **Simplify your code** by not duplicating metric logic and allowing MetricFlow to perform complex calculations for you. +- **Empower stakeholders** with rich context and flexible, yet governed experiences. + + + + + +dbt Metrics is the now-deprecated dbt package that was used to define metrics within dbt. dbt Metrics has been replaced with [MetricFlow](/docs/build/about-metricflow), a more flexible and powerful engine, which powers the foundation of the dbt Semantic Layer today. + +MetricFlow introduces SQL generation to the dbt Semantic Layer and offers more advanced capabilities than dbt Metrics, for example: + +- **Query construction** — MetricFlow iteratively constructs queries using a dataflow plan, our internal DAG for generating SQL. By comparison, dbt Metrics relied on templated Jinja to construct SQL. +- **Joins** — MetricFlow also has a sophisticated way of handling joins, which dbt Metrics did not support. With MetricFlow you can effortlessly access all valid dimensions for your metrics on the fly, even when they are defined in different semantic models. + + + + + +Yes, absolutely! Join the [dbt Slack community](https://app.slack.com/client/T0VLPD22H) and [#dbt-cloud-semantic-layer](https://getdbt.slack.com/archives/C046L0VTVR6) slack channel for all things related to the dbt Semantic Layer. + + + + + +The dbt Semantic Layer is flexible enough to work with many common modeling approaches. It references dbt models, which means how you configure your Semantic Layer will mirror the modeling approach you've taken with the underlying data. + +The primary consideration is the flexibility and performance of the underlying queries. For example: + +- A star schema data model offers more flexibility for dimensions that are available for a given metric, but will require more joins. +- A fully denormalized data model is simpler, will be materialized to a specific grain, but won’t be able to join to other tables. + +While the dbt Semantic Layer will work for both cases, it's best to allow MetricFlow do handle some level of denormalization for you in order to provide more flexibility to metric consumers. + + + + +The dbt Semantic Layer measures usage in distinct 'Queried Metrics'. Refer to the [Billing](/docs/cloud/billing#what-counts-as-a-queried-metric) to learn more about pricing. + + +## Availability + + + +Yes, the dbt Semantic Layer is compatible with [dbt v1.6 or higher](/docs/dbt-versions/upgrade-dbt-version-in-cloud). + + + + +Yes, dbt Cloud [Enterprise or Team](https://www.getdbt.com/pricing) plan customers can access the dbt Semantic Layer. + + + + +The dbt Semantic Layer is proprietary to dbt Cloud, however some components of it are open-source. dbt Core users can use MetricFlow features, like defining metrics in their projects, without a dbt Cloud plan. + +dbt Core users can also query their semantic layer locally using the command line. However, they won't be able to use the [APIs](/docs/dbt-cloud-apis/sl-api-overview) or [available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) to access metrics dynamically. + + + + + +If you're interested in the this type of implementation, please reach out to us [here](https://www.getdbt.com/get-started). + + +## How does the dbt Semantic Layer work? + + + +You can use tables and dbt models to calculate metrics as an option, but it's a static approach that is rigid and cumbersome to maintain. That’s because metrics are seldom useful on their own: they usually need dimensions, grains, and attributes for business users to analyze (or slice and dice) data effectively. + +If you create a table with a metric, you’ll need to create numerous other tables derived from that table to show the desired metric cut by the desired dimension or time grain. Mature data models have thousands of dimensions, so you can see how this will quickly result in unnecessary duplication, maintenance, and costs. It's also incredibly hard to predict all the slices of data that a user is going to need ahead of time. + +With the dbt Semantic Layer, you don’t need to pre-join or build any tables; rather, you can simply add a few lines of code to your semantic model, and that data will only be computed upon request. + + + + +No, you don't. When querying the dbt Semantic Layer through the [Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview), you're not materializing any data by default. + +The dbt Semantic Layer dynamically computes the metric using the underlying data tables. Then it returns the output to the end user. + + + + +The dbt Semantic Layer does not store a physical copy of your data. It uses underlying tables to construct or compute the requested output. + + + + +MetricFlow is hosted in dbt Cloud. Requests from the [Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview) are routed from our API gateway to MetricFlow, which generates the SQL to compute what's requested by the user. MetricFlow hands the SQL back to our gateway, which then executes it against the data platform. + + + + +1. You define [semantic models](/docs/build/semantic-models) in YAML files that describe your data, including entities (for joins), measures (with aggregation types as a building block to your metrics), and dimensions (to slice and dice your metrics). + +2. Then you build your metrics on top of these semantic models. This is all done in `.yml` configurations alongside your dbt models in your projects. +3. Once you've defined your metrics and semantic models, you can [configure the dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-sl) in dbt Cloud. + +Read our [Quickstart](/docs/use-dbt-semantic-layer/quickstart-sl) for more information. + + + + + +Beginning in March 2024, the dbt Semantic Layer will offer two layers of caching: + +- The result cache which is a Redis cache. +- A declarative cache which lives in your data platform. + + + + + +No, the dbt Semantic Layer is flexible enough to work with many data modeling approaches including Snowflake, Star schemas, Data vaults, or other normalized tables. + + + + +MetricFlow always tries to generate SQL in the most performant way, while ensuring the metric value is correct. It generates SQL in a way that allows us to add optimizations, like predicate pushdown, to ensure we don’t perform full table scans. + + + + + +The latency of query runtimes is low, in the order of milliseconds. + + + + + +If the underlying metric aggregation is different, then these would be different metrics. However, if teams have different definitions because they're using specific filters or dimensions, it's still the same metric. They're just using it in different ways. + +This can be managed by adjusting how the metric is viewed in downstream tools or setting up [saved queries](/docs/build/saved-queries) to handle the various permutations of it. + + + +## Build metrics and semantic models + + + +MetricFlow does not currently support custom aggregations on measures. You can find supported aggregation types [here](/docs/build/measures#aggregation). + + + + + +[Joins](/docs/build/join-logic) are identified through [entities](/docs/build/entities) defined in a [semantic model](/docs/build/semantic-models). These are the keys in your dataset. You can specify `foreign`, `unique`, `primary`, or `natural` joins. + +With multiple semantic models and the entities within them, MetricFlow creates a graph using the semantic models as nodes and the join paths as edges to perform joins automatically. MetricFlow chooses the appropriate join type and avoids fan-out or chasm joins with other tables based on the entity types. You can find supported join types [here](/docs/build/join-logic#types-of-joins). + + + + +Expr (short for “expression”) allows you to put any arbitrary SQL supported by your data platform in any definition of a measure, entity, or dimension. + +This is useful if you want the object name in the semantic model to be different than what it’s called in the database. Or if you want to include logic in the definition of the component you're creating. + +The MetricFlow spec is deliberately opinionated, and we offer “expr” as an escape hatch to allow developers to be more expressive. + + + + +Yes, we approach this by specifying a [dimension](/docs/build/dimensions) that a metric cannot be aggregated across (such as `time`). You can learn how to configure semi-additive dimensions [here](/docs/build/measures#non-additive-dimensions). + + + + +Yes, while [entities](/docs/build/entities) must be defined under “entities,” they can be queried like dimensions in downstream tools. Additionally, if the entity isn't used to perform joins across your semantic models, you may optionally define it as a dimension. + + +## Available integrations + + + +There are a number of data applications have integrations with the dbt Semantic Layer, including Tableau, Google Sheets, Hex, and Mode, among others. + +Refer to [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) for more information. + + + + + +You can use [exports](/docs/use-dbt-semantic-layer/exports) to materialize your metrics into a table or view in your data platform. From there, you can connect your visualization tool to your data platform. + +Although this approach doesn't provide the dynamic benefits of the dbt Semantic Layer, you still benefit from centralized metrics and from using MetricFlow configurations to define, generate, and compute SQL for your metrics. + + + + + +Creating an [export](/docs/use-dbt-semantic-layer/exports) allows you to bring your governed metric definitions into your data platform as a table or view. This means your metric logic is managed centrally in dbt, instead of as a view in your data platform and ensures that metric values remain consistent across all interfaces. + + + + + +Yes, all of our interfaces or APIs expose metric descriptions, which you can surface in downstream tools. + + + +## Permissions and access + + + +Currently, the credentials you configure when setting up the dbt Semantic Layer are used for every request. Any physical access policies you have tied to your credentials will be respected. + +We are currently working on introducing more fine-grained access controls, including user-level access and group credentials, that enable flexible granular permissions. + + +## Implementation + + + +We recommend to build your semantic layer on top of the [marts layer](/best-practices/how-we-structure/5-semantic-layer-marts), which represents the clean and transformed data from your dbt models. + + + + +Semantic layer credentials are different than the credentials you use to run dbt models. Specifically, we recommend a less privileged set of credentials since consumers are only reading data. + + + + +Currently, semantic models can be created from dbt models that live across projects ([dbt Mesh](/best-practices/how-we-mesh/mesh-1-intro)). In the future, users will also be able to use mesh concepts on semantic objects and define metrics across dbt projects. + + + + +If you're using the legacy Semantic Layer, we highly recommend you [upgrade your dbt version](/docs/dbt-versions/upgrade-dbt-version-in-cloud) to dbt v1.6 or higher to use the latest dbt Semantic Layer. Refer to the dedicated [migration guide](/guides/sl-migration) for more info. + diff --git a/website/docs/guides/sl-migration.md b/website/docs/guides/sl-migration.md index afa181646e3..f686c15307a 100644 --- a/website/docs/guides/sl-migration.md +++ b/website/docs/guides/sl-migration.md @@ -131,6 +131,7 @@ If you created a new environment in [Step 3](#step-3-setup-the-semantic-layer-in ### Related docs +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) - [MetricFlow quickstart guide](/docs/build/sl-getting-started) - [Example dbt project](https://github.com/dbt-labs/jaffle-sl-template) - [dbt metrics converter](https://github.com/dbt-labs/dbt-converter) diff --git a/website/docs/guides/sl-partner-integration-guide.md b/website/docs/guides/sl-partner-integration-guide.md index c55bd83cec1..7bb3d4b0e42 100644 --- a/website/docs/guides/sl-partner-integration-guide.md +++ b/website/docs/guides/sl-partner-integration-guide.md @@ -166,7 +166,7 @@ These are recommendations on how to evolve a Semantic Layer integration and not ### Related docs - +- [dbt Semantic Layer FAQs](/docs/use-dbt-semantic-layer/sl-faqs) - [Use the dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) to learn about the product. - [Build your metrics](/docs/build/build-metrics-intro) for more info about MetricFlow and its components. - [dbt Semantic Layer integrations page](https://www.getdbt.com/product/semantic-layer-integrations) for information about the available partner integrations. diff --git a/website/sidebars.js b/website/sidebars.js index 6cb0c656079..df02241aa31 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -490,9 +490,10 @@ const sidebarSettings = { "docs/use-dbt-semantic-layer/setup-sl", "docs/use-dbt-semantic-layer/exports", "docs/use-dbt-semantic-layer/sl-architecture", + "docs/use-dbt-semantic-layer/sl-faqs", { type: "category", - label: "Integrations", + label: "Available integrations", link: { type: "doc", id: "docs/use-dbt-semantic-layer/avail-sl-integrations" }, items: [ "docs/use-dbt-semantic-layer/avail-sl-integrations", diff --git a/website/src/components/expandable/styles.module.css b/website/src/components/expandable/styles.module.css index dd6c94770d1..9345b7986e3 100644 --- a/website/src/components/expandable/styles.module.css +++ b/website/src/components/expandable/styles.module.css @@ -1,6 +1,6 @@ :local(.link) :local(.headerText) { content: ''; - color: black; /* Black text in normal mode */ + color: rgba(18, 12, 12, 0.862); /* Black text in normal mode */ text-decoration: none; transition: text-decoration 0.3s; /* Smooth transition */ font-weight: 600; @@ -38,7 +38,7 @@ /* Adjusting for Light and Dark Modes */ :local(html[data-theme='dark'] .link), :local(html[data-theme='dark'] .headerText) { - color: white; /* White text in dark mode */ + color: rgba(255, 255, 255, 0.696); /* White text in dark mode */ } :local(html[data-theme='dark'] .toggle)::before { @@ -55,7 +55,7 @@ :local(html[data-theme='dark'] .link), :local(html[data-theme='dark'] .headerText) { - color: white; /* White text in dark mode */ + color: rgba(255, 255, 255, 0.801); /* White text in dark mode */ } :local(.body > p:last-child) {