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Add Extrica adapter documentation to DBT docs #4616

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extricatrianz
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@extricatrianz extricatrianz commented Dec 9, 2023

What are you changing in this pull request and why?

Description & Motivation

This pull request introduces the dbt-extrica adapter, an innovative addition to the dbt ecosystem designed to seamlessly integrate data mesh principles into the dbt workflow.

By building an adapter on top of dbt Core, we aim to extend the reach of the Extrica use case to a wider audience within the dbt community. The adapter is now available on the PyPI.

Key Features

  • The dbt-extrica adapter acts as a bridge between dbt Core and the extrica data mesh solution, facilitating data integration, transformation, modeling, and analysis from diverse data sources.
  • Data Mesh Integration: Enables users to seamlessly integrate and model data from multiple sources, aligning with the principles of data mesh architecture.
  • Comprehensive Transformation & Ease of Use: Supports complex data transformations to derive meaningful insights for analysis and reporting. The adapter is designed with user convenience in mind, ensuring a smooth and intuitive experience for dbt users.

Validation of Models

This contribution has undergone rigorous testing to ensure its reliability and effectiveness. The adapter has been validated in real-world scenarios to guarantee its performance in diverse environments.

Running Test Cases

Screenshot (308)

Checklist

  • The adapter is hosted on GitHub.
  • the dbt-extrica adapter is published PyPI.

Adding new pages:

  • The page has been added to website/sidebars.js
  • Provided a unique filename for the new page (extrica-configs for configuration and extrica-setup for setup)
  • Created setup file under /docs/core/connect-data-platform/extrica-setup.md
  • Created config file under reference/resource-configs/extrica-configs.md
  • Added Extrica under docs/community-adapters.md.

@extricatrianz extricatrianz requested review from dataders and a team as code owners December 9, 2023 07:34
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welcome bot commented Dec 9, 2023

Hello!👋 Thanks for contributing to the dbt product documentation and opening this pull request! ✨
We use Markdown and some HTML to write the dbt product documentation. When writing content, you can use our style guide and content types to understand our writing standards and how we organize information in the dbt product docs.
We'll review your contribution and respond as soon as we can. 😄

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@runleonarun runleonarun added the new contributor Label for first-time contributors label Dec 9, 2023
@github-actions github-actions bot added content Improvements or additions to content size: medium This change will take up to a week to address labels Dec 9, 2023
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