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sfc-gh-bklein authored Oct 4, 2024
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Expand Up @@ -11,16 +11,25 @@ The purpose of the code is to provide customers with easy access to innovative i

Please see TAGGING.md for details on object comments.

## Solutions

| Solution | Description |
| --- | --- |
| [Supply Chain Network Optimization](https://github.com/Snowflake-Labs/sfguide-supply-chain-network-optimization/) | Using optimization programming to make least cost fulfillment decisions. |
| [Solution Installation Wizard](https://github.com/Snowflake-Labs/sfguide-solution-installation-wizard/) | A Native App that helps facilitate consumers deploy code from the provider. |
| [Alert Hub](https://github.com/Snowflake-Labs/sfguide-alert-hub/) | A Streamlit for managing and templatizing Alerts. |
| [Application Control Framework](https://github.com/Snowflake-Labs/sfguide-application-control-framework/) | A framework that allows for rule-based access and consumer experiences within Native Apps. |
| [Data Crawler](https://github.com/Snowflake-Labs/sfguide-data-crawler/) | A solution prompting a Cortex Large Language Model (LLM) to generate a natural language description of each table within a database and/or schema. |
| [Cohort Builder](https://github.com/Snowflake-Labs/sfguide-cohort-builder/) | The Cohort Builder Model leverages Snowflake and Snowpark to create, manage, and schedule cohorts effectively. |
| [API Enrichment Framework](https://github.com/Snowflake-Labs/sfguide-getting-started-with-api-enrichment-framework/) | A Native App designed to quick start API-driven data enrichment. |
| [Data Quality Manager](https://github.com/Snowflake-Labs/sfguide-getting-started-with-data-quality-manager/) | A application designed to implement data quality checks, using both Snowflake data metric functions (DMFs) and custom checks. |
| [ML (Machine Learning) Sidekick](https://github.com/Snowflake-Labs/sfguide-build-and-deploy-snowpark-ml-models-using-streamlit-snowflake-notebooks/) | A no-code app built using Streamlit in Snowflake, designed for building and deploying machine learning models in Snowflake. |

## Solution Types
A solution can represent one of three types:

* FRAMEWORK - A configurable solution meant for continuous use, augmenting the Snowflake experience
* HELPER - A typically lightweight utility meant to be used as-needed for specific tasks
* DEMO - An example meant to be used to understand a topic using synthetic data


## Solution List

| Solution | Type | Description |
| --- | --- | --- |
| [Supply Chain Network Optimization](https://github.com/Snowflake-Labs/sfguide-supply-chain-network-optimization/) | DEMO | A solution using optimization programming to make least cost fulfillment decisions. |
| [Solution Installation Wizard](https://github.com/Snowflake-Labs/sfguide-solution-installation-wizard/) | FRAMEWORK | A Native App that helps facilitate consumers deploy code from the provider. |
| [Alert Hub](https://github.com/Snowflake-Labs/sfguide-alert-hub/) | FRAMEWORK | A Streamlit for managing and templatizing Alerts. |
| [Application Control Framework](https://github.com/Snowflake-Labs/sfguide-application-control-framework/) | FRAMEWORK | A framework that allows for rule-based access and consumer experiences within Native Apps. |
| [Data Crawler](https://github.com/Snowflake-Labs/sfguide-data-crawler/) | FRAMEWORK | A solution prompting a Cortex Large Language Model (LLM) to generate a natural language description of each table within a database and/or schema. |
| [Cohort Builder](https://github.com/Snowflake-Labs/sfguide-cohort-builder/) | FRAMEWORK | The Cohort Builder Model leverages Snowflake and Snowpark to create, manage, and schedule cohorts effectively. |
| [API Enrichment Framework](https://github.com/Snowflake-Labs/sfguide-getting-started-with-api-enrichment-framework/) | FRAMEWORK | A Native App designed to quick start API-driven data enrichment. |
| [Data Quality Manager](https://github.com/Snowflake-Labs/sfguide-getting-started-with-data-quality-manager/) | FRAMEWORK | An application designed to implement data quality checks, using both Snowflake data metric functions (DMFs) and custom checks. |
| [ML (Machine Learning) Sidekick](https://github.com/Snowflake-Labs/sfguide-build-and-deploy-snowpark-ml-models-using-streamlit-snowflake-notebooks/) | FRAMEWORK | A no-code app built using Streamlit in Snowflake, designed for building and deploying machine learning models in Snowflake. |

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