Quasar is a newly launched platform that has generated a lot of buzz in the blockchain and crypto world. It is a decentralized finance (DeFi) platform that provides users with a seamless and efficient way to manage their digital assets. Quasar aims to solve some of the most pressing issues in DeFi, such as high transaction fees, slow transaction speeds, and limited asset liquidity.

Recently, there has been a significant flow of assets from Osmosis, another popular DeFi platform, to Quasar. This movement of assets has been driven by several factors, including Quasar's unique features, such as its user-friendly interface, fast transaction speeds, and low fees. Additionally, Quasar has gained a reputation for being highly secure and reliable, which has further increased investor confidence in the platform.

This shift in asset flows from Osmosis to Quasar has also been facilitated by the interoperability of these platforms. Quasar and Osmosis are both built on the Cosmos SDK, which allows them to interoperate seamlessly. This means that users can easily transfer assets between the two platforms without incurring significant fees or delays.

Overall, Quasar's recent launch and the subsequent movement of assets from Osmosis are clear indications of the growing demand for innovative and efficient DeFi platforms. With its cutting-edge technology, user-friendly interface, and strong community support, Quasar is poised to become a leading player in the DeFi space in the coming years.

In this dashboard, i made an analysis about asset flows from Osmosis to Quasar, a new platform which launched 2 weeks ago on March 23th 2023. We will take a look at trasnfers between these platforms, senders and their activity and their performance during this period.

I extracted the data from Flipsidecrypto database and Osmosis.core schema and filtered senders from Osmosis with SUBSTR(sender,0,4) ilike 'osmo' .

It seems wallets on Quasar starts with quasar itself, so i filtered them in this way: SUBSTR(receiver, 0, 6) ilike 'quasar'

Also i filtered these transactions with transfer_type = 'IBC_TRANSFER_OUT' and considered only successful transactions with TX_SUCCEEDED = 'true' to make the data more concise and clear.

I found out that the amount section in fact_transfers table is representing transfer fees so i calculated the sent usd volume from msg_attributes table.