# Home

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This website is currently in construction. Please bear with us and don't hesitate to[ reach out to the AWG in discord for any questions.](https://discordapp.com/channels/790157548845924352/848225246443470848)
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On March 9, 2022, Inverse Finance holders voted for the launch of the **Analytics Working Group** (AWG) within the DAO to support our growth, define further and execute the Data Strategy as per [proposal 7 of Mills era.](https://www.inverse.finance/governance/proposals/mills/7)

<figure><img src="https://4269815422-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGc9mnST31tkU3h2NNgSL%2Fuploads%2FhqaO6biJv9OQc4VUCtwg%2FUntitled%20design(1).png?alt=media&#x26;token=eb02739f-b9e2-4fc2-9888-3459f27e5887" alt="" width="375"><figcaption></figcaption></figure>

The main goal of the AWG is to enable members and users to seamlessly **access the data of their interest**, and to be able to **use it in the environment of their choice**. Because of all the tools and range of skills involved in the space, it is not always an easy task to do so.

Within that perspective, the Analytics Working Group provides our members and users with the following :&#x20;

[**​Dynamic Dashboards :**](https://docs.inverse.watch/products/inverse-watch) based on **PostgreSQL** queries and relying on **an in house** flexible environment (forked from Redash), allowing on-the-fly analysis and CSVs extractions for specific or urgent needs ;​

[**GraphQL endpoints :**](https://docs.inverse.watch/products/inverse-subgraphs) based on **The Graph** enabling to index on-chain events as soon as they happen and making the protocol information accessible to everyone through a **GraphQL endpoint ;**&#x200B;

[**Alert and Social notifications :**](https://docs.inverse.watch/products/inverse-alerts) thanks to our extensive infrastructure we are able to display beautiful notifications and alerts in Discord or Twitter, from any data source.

Inverse Watch is a platform created by the AWG with the goal of centralizing its services, and make data analytics tasks less repetitive and more efficient in order to better serve the DAO.


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