Add dbt-metalog from Indicium to hub.json

[bruno-szdl]

Description

Have you ever found yourself jotting down essential business rules, questions, technical owners, or ToDos in a separate Excel sheet  - far from your code -, only to forget about them later?

Do you struggle to keep track of all the metadata that's critical for effective data management and analysis?

Worry no more! We have a solution - dbt-metalog.

Create light customizable models from your metadata.

Easily create models for:

✅ Business rules.

✅ Business questions.

✅ Tech owners.

✅ Requesting areas/persons.

✅ Date the model was created.

✅ ToDo's.

✅ Any metadata you want...

Choose your metadata by:

✅ name.

✅ resource type.

✅ file.

This package only contains macros and does not use any adapter-specific method or config.

Link to your package's repository: https://github.com/techindicium/dbt-metalog

Checklist

This checklist is a cut down version of the best practices that we have identified as the package hub has grown. Although meeting these checklist items is not a prerequisite to being added to the Hub, we have found that packages which don't conform provide a worse user experience.

First run experience

• [X] The package includes a README which explains how to get started with the package and customise its behaviour
• [ ] The README indicates which data warehouses/platforms are expected to work with this package

Customisability

• [ ] The package uses ref or source, instead of hard-coding table references.

  Packages for data transformation (delete if not relevant):

• [ ] provide a mechanism (such as variables) to customise the location of source tables.
• [ ] do not assume database/schema names in sources.

Dependencies

Dependencies on dbt Core

• [X] The package has set a supported require-dbt-version range in dbt_project.yml. Example: A package which depends on functionality added in dbt Core 1.2 should set its require-dbt-version property to [">=1.2.0", "<2.0.0"].

  Dependencies on other packages defined in packages.yml:

• [ ] Dependencies are imported from the dbt Package Hub when available, as opposed to a git installation.
• [ ] Dependencies contain the widest possible range of supported versions, to minimise issues in dependency resolution.
• [ ] In particular, dependencies are not pinned to a patch version unless there is a known incompatibility.

  Interoperability

• [X] The package does not override dbt Core behaviour in such a way as to impact other dbt resources (models, tests, etc) not provided by the package.
• [ ] The package uses the cross-database macros built into dbt Core where available, such as {{ dbt.except() }} and {{ dbt.type_string() }}.
• [ ] The package disambiguates its resource names to avoid clashes with nodes that are likely to already exist in a project. For example, packages should not provide a model simply called users.

Versioning

• [X] (Required): The package's git tags validates against the regex defined in version.py
• [X] The package's version follows the guidance of Semantic Versioning 2.0.0. (Note in particular the recommendation for production-ready packages to be version 1.0.0 or above)