Bubblemaps: Making Blockchain Data Analysis Less Complicated
In the complex world of blockchain data analysis, many people often feel overwhelmed by the vast amounts of data. However, today I want to introduce you to Bubblemaps, an innovative tool that serves as a magical key, opening the door to blockchain data for us.
Bubblemaps can transform complex on-chain data into intuitive bubble charts, whether auditing DeFi tokens or analyzing the supply distribution of NFTs, it can handle it with ease. It supports multiple blockchains such as Ethereum and BNB Chain, allowing both beginners and seasoned blockchain players to quickly explore wallet relationships, token holdings, and historical changes. Its user-friendly interface greatly simplifies the analysis process in the crypto market, providing users with more comprehensive market insights.
The core advantage of Bubblemaps lies in its outstanding visual design. It presents complex blockchain data as colorful bubble charts, where each bubble represents a wallet, the size of the bubble is proportional to the amount of tokens held, and the dashed lines between bubbles display transfer records, helping us reveal potential relationships.
It also has many practical features. The clear and straightforward interface allows beginners to easily understand blockchain data; by clicking on a bubble, users can view the token proportion, ranking, and holding details of the wallet. The platform defaults to showing the top 150 major wallets to avoid information overload; advanced accounts also have a time travel feature, allowing users to trace back wallet balances and connection changes; wallets with transfer history can be identified by bubbles of the same color, helping us discover behaviors of holding through multiple wallets.
Overall, Bubblemaps lowers the barrier for utilizing on-chain data, enabling more people to delve into fields like DeFi, NFTs, and Meme coins without requiring a professional technical background. It is an excellent alternative to traditional browsers, promoting transparent interpretation of data.
