Web3 Data Analytics: Unraveling the Power of Decentralized Data
What if you could harness the galactic amounts of data transacted on blockchain networks every second into pieces of information that give you an overview of the market?
In this course, we’re venturing beneath the surface of web3, breaking down the facets of data analytics, and diving into how you can harness this alpha to your advantage.
What is Web3 Data Analytics?
Web3 data is the blockchain-based (decentralized) information stored on a network of nodes. It’s the trustless and transparent data transactions that power the existing web3 ecosystem. Web3 data analytics, however, is the process of collecting, organizing, and analyzing the raw data collected on blockchain networks, converting it into valuable insights that form the foundation of prediction models and drive data-oriented decisions.
Fundamentally, web3 data analytics have similar characteristics to web2 data analytics, but it introduces an additional dimension in which the data is inherently public, immutable, and distributed across a global network of nodes. Ergo, navigating through large datasets of on-chain data typically requires a specific set of proficiency. To illustrate, the data collected from blockchain networks typically include transaction values, active addresses, smart contract interactions, participation rates, or credentials across dApps, NFTs, and DeFi platforms.
Who Needs Web3 Data Analytics?
Regardless of your objective in web3, having data analytics in your toolbox provides an extra level of competitive edge. Here is how each group of users can maximize the capabilities of data analytics.
Developers and project teams: Web3 projects need analytics to form a comprehensive overview of how their applications are being used. Ranging from tracking smart contract interactions, monitoring gas usage, and analyzing user activities, these data points are often the root of future functionality developments that refine the end-user experience.
Investors and traders: Through analytics, investors and traders can find historical market data of cryptocurrencies and DeFi products, which can shape the basis of a price prediction model. These specifics include tracking token metrics, liquidity in DeFi pools, and yield farming opportunities that grant a quantitative edge, aka alpha.
Regulatory and compliance bodies: With the decentralized nature of blockchains, regulatory oversight poses additional challenges to regulators and authorities. Analytics tools can help official bodies monitor transactions for compliance with legal standards, identify malicious activities, and ensure the integrity of financial transactions on the blockchain.
Academic researchers: Scholars and researchers can utilize web3 data analytics to study the economic, social, and technological impacts of blockchain technology or form predictive models. This research often drives further innovation and understanding of the space.
Casual users and enthusiasts: Casual users of web3 benefit from a comprehensive overview of trends across the industry as it enables a more in-depth understanding of the industry and individual projects.