Dapplooker is Celebrated as the First Graduate from the SubQuery Grants Programme

Today we are proud to highlight the phenomenal work of our first SubQuery Grants Programme graduate! Dapplooker have integrated with SubQuery so that beautiful and easy-to-build analytic tools such as explorers, charts and dashboards can be built on top of any SubQuery dataset.

Whether a SubQuery project was built by you or someone else in the community, you can use DappLooker to graph, chart, and visualise the data from within it. Until now, SubQuery’s managed service only provided a GraphQL endpoint, but with Dapplookers innovation you can now more easily explore hundreds of datasets and do analytics on SubQuery data using intuitive “Visual SQL”.

One of the best parts about this business intelligence tool is that you do not have to be technical to use it and Dapplooker have provided straightforward documentation to assist users starting out on the platform. Furthermore, the Dapplooker team have also used two existing SubQuery data sets to create useful dashboards with Moonbeam staking data and Polkadot crowdloans that show off the potential of the tool.

“We founded DappLooker to make blockchain data accessible so even non-technical users can easily create charts and dashboards to visualise information. Thanks to the SubQuery Grants Programme we are now able to provide more value to the Polkadot ecosystem with our integration and we can’t wait to see how people use it. As we progressed through our Grant milestones, the SubQuery team were fantastic to work with as they solved any query we had including solving technical challenges very quickly.”

- Abhinav, Co-Founder, DappLooker

While previously reporting and analytics may have fallen out of scope as a priority item, this integration gives projects the ability to write SQL queries to create invaluable insights using Dapplooker’s easy-to-use visual editor.

For example, you can use the existing Polkadot crowdloan auction dataset in dAppLooker and create a dashboard with a key focus on the retention of contributors across the auctions.

This example dashboard uses SubQuery’s indexed Moonbeam EVM data and highlights peaks and troughs as well as success versus failed transactions in the Moonbeam network.

“We knew right away we wanted to accept Dapplooker into the SubQuery Grants Programme as their values aligned so closely with ours and there was an obvious benefit for us to combine forces. We both endeavour to provide efficiencies for Dapp developers so they can focus on their mission and not spend wasted time building back-end solutions. Now with Dapplooker, teams can leverage their easy to use platform to access analytics and reporting of on-chain data.”

— Brittany Seales, SubQuery Grants Programme Lead

To leverage Dapplooker today, head to the SubQuery integration home page to log-in (or sign-up for free) and select the data set you would like to build your dashboard from. After using the step-by-step documentation, you can search directly for the relevant SubQuery project in the ‘SubQuery Project Endpoint’ field on Dapplooker or locate this directly in our Explorer to be copied over.

About Dapplooker:

Dapplooker is a multi-chain analytics and visualization platform for blockchain networks and Dapps. Our aim is to empower people by making analysis of blockchain data simple with the aid of easy-to-use visual editor. Users can run SQL queries on smart contract data, build charts and dashboards which can be shared with the community.

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About SubQuery

SubQuery is a blockchain developer toolkit enabling others to build Web3 applications of the future. A SubQuery project is a complete API to organise and query data from layer-1 chains. Currently servicing Polkadot , Substrate and Avalanche projects, this data-as-a-service allows developers to focus on their core use case and front-end, without needing to waste time on building a custom backend for data processing. The SubQuery Network proposes to enable this same scalable and reliable solution, but in a completely decentralised way.

Find Out More

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