Big Data Analysis on Blockchain with CEO of Covalent, Ganesh Swami

I sat down with Ganesh Swami, co-founder and CEO at Covalent, a Blockchain Big Data analytics firm, to discuss the Ethereum ecosystem.

Ishan Pandey: Hi, Welcome to our “Behind the Startup” Series. Please tell us about yourself and the story behind Covalent?

Ganesh Swami: Hi guys, thank you for having me. I’m Ganesh, a serial entrepreneur and a physicist by training. I have spent much of my career thus far in the data space across a number of industries, including pharmaceuticals, cloud computing, and now blockchain technology.

In 2017, my co-founder Levi and I had the foresight that transparency is crucial for this industry to reach mass adoption and fully realize the potential of crypto. In an effort to increase transparency, we saw there was an opportunity to build a solution that would tackle the challenges of blockchain data. That solution is Covalent today.

Ishan Pandey: Even though data on a blockchain is freely available. Why is it still difficult for users to access data and perform analytics on it for business uses?  

Ganesh Swami: Blockchain data is freely available. However, since there are so many different protocols, chains, projects, and products, each produces data in various formats and the data rarely follows any standard, causing unnecessary complexities. This lack of standardization and complexity means that developers and traders alike must sink considerable resources into analyzing data. Our belief is that this problem has to be solved before blockchain-based products are attractive to mainstream users.

Ishan Pandey: What kind of target audience generally leverages data related to blockchain ecosystems?  

Ganesh Swami: Anyone who relies on data to make a decision is part of the target audience. Typically, it’s been analysts, investors, and traders. However, given that Covalent not only offers a wide range of rich data services that comes from indexing the entire blockchain, we also have a no-code solution. This drastically increases the availability and appetite for blockchain data. As a result, we see this audience expanding greatly, ranging from educational institutions all the way to healthcare.

Ishan Pandey: Please share some interesting insights and trends that you have identified by using data analytics?

Ganesh Swami: We don’t dictate how our customers use the data. And oftentimes, we are surprised by the diverse insights our customers gather from deep, granular data. Taking Uniswap as an example, investors have used Covalent to do rich due diligence on the 20,000 available liquidity pools. Here’s a sample of what they’ve done:

Ishan Pandey: How can yield farmers use big data to make actionable decisions?

Ganesh Swami: I think yield farmers are going after the most returns without any regard for risk. As the space levels up, I think yield farmers can make conscious, data-driven decisions factoring in both risk as well as reward.

We are already working with 2-3 risk analytics providers to bring this level of sophistication to the DeFi space.

Ishan Pandey: How can developers use Ethereum data for building successful Decentralized applications and spotting future market trends?

Ganesh Swami: Developers need to make a conscious decision to target either power users or novice users. For power-users, DApp developers can show a lot of data during the decision making process in order to inform. For novice users, DApp developers can use data to highlight the best and second-best choices when it comes to a decision.

For example, a very popular wallet uses Covalent to show the profitability of various pools over time right in the UI when the investor/trader is making a decision. I think this is the future, and it’s exciting to see it play out in front of our eyes.

Ishan Pandey: Do custodians and exchanges use data analytics? If so, what is the objective behind it?

Ganesh Swami: Absolutely, data is a key offering for both custodians as well as exchanges and we have customers of both kinds. In the exchange space, Covalent offers basically the data portion of what a trader would see on a centralized exchange like Coinbase, for example, historical transaction activity, PnL, and other record-keeping use-cases.

With custodians, it’s coming down to a value-added service. No custodian wants to remain just a custodian but wants to differentiate themselves amongst their competitors. Some custodians are starting to add yield generating activity with the assets, participate in securing proof-of-stake networks, etc. Data plays a huge role in providing a good user experience to their end-users.

Ishan Pandey: What are your views on the problem of scalability and high transaction fees that Ethereum is currently facing?

Ganesh Swami: In my opinion, scalability and high transaction fees will get solved within the next 24 months. The solution comes from layer 2, scaling solutions that use Ethereum for base-layer security. We are already working with Matic, Skale, Loopring, zkSync, Optimistic, and others who are currently on mainnet or will launch on mainnet within the next few weeks.

Ishan Pandey: How can big data be used to analyze money laundering and other illicit activities?

Ganesh Swami: This analysis falls under a field called “financial forensics,” and there are many players in the space who focus on selling big data solutions to 3-letter agencies. Covalent doesn’t focus much on this use-case because most illicit activities happen on smaller and niche chains.

Some use-cases overlap with other kinds of risk metrics we alluded to in an earlier answer. For example, a wallet is risky if:

You can see the recent news on how stolen/hacked funds were recovered because the hacker tried to off-load the funds without carefully covering their tracks.

Ishan Pandey: What future trends and challenges do you see in 2021 for the Ethereum ecosystem?

Ganesh Swami: A couple of huge innovations on the horizon: