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The Promises and Challenges of Data on DeFi

4 mins
Updated by Ana Alexandre
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In Brief

  • The DeFi ecosystem, particularly decentralized exchanges, has now filled a gap that centralized exchanges simply don’t.
  • The tools available still don’t go far enough yet to provide traders with all of the data they need.
  • Since centralized exchanges are custodians of their own data, you have to trust that they are publishing accurate data.
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Decentralized finance (DeFi) has unlocked direct access to data on blockchain networks. There are, however, still relatively few products taking advantage of this new treasure trove of information.

The DeFi ecosystem, particularly decentralized exchanges (DEXs), has now filled a gap that centralized exchanges (CEXs) simply don’t. While CEXs provide rich data about the overall market, including data about individual trades, DEX transactions take place on chain, meaning you can track individual wallets and their activity.

DEXs open up an API for people to acquire data to make statistical decisions when trading on an automated basis, as well as to pull exchange data so that traders can do their own offline analysis or run bots. This provides a deeper understanding of the trading environment, which allows traders to find out who is making a given trade and to analyse individual trader activity. 

That wasn’t really possible when Uniswap first launched, because there was just a lack of products to enable that. And so a handful of people — those who knew how Uniswap ticked — enjoyed an early advantage.

Up until the first charting platforms came along, that is. We learned that, even in the absence of centralized tools, these markets were still behaving somewhat rationally as decentralized markets. Traditional technical analysis and indicators, such as volume and trading patterns, remained relevant. 

But the tools available still don’t go far enough yet to provide traders with all of the data they need. There is a game of cat and mouse in progress. Uniswap, for example, indirectly hosts an API using a product called The Graph, which is an indexing protocol for querying networks like Ethereum and IPFS.

With The Graph, anyone can build and publish open APIs, called subgraphs, to make data easily accessible. It is a very powerful product, but at times it runs 30 seconds to a minute behind trades. So, that in and of itself is problematic. When you make trading decisions, you can’t guarantee that the conditions upon which you based your decision are still true and relevant.

Let’s say you’re looking for a price trigger, for example, and data trickles through on the subgraph showing a particular ticker is now trading at a certain price. And then you go and buy or sell based on the perceived trading opportunity.

You execute the trade only to learn the conditions have changed. Unlike centralized exchanges, you don’t have order books, so it’s quite difficult to know exactly the price you’re going to get. You risk placing the trade too high, too low, or being front run by bots, etc.

Making informed decisions

As a trader, your job is to make informed decisions based on the data and intelligence that you’re able to gather. If you are gathering intelligence and data from a source that is running a minute behind, there’s a risk that the situation that you are planning to trade no longer exists.

This then creates an arbitrage which gives an advantage to those who have access to their own, faster data technologies, which allow them to take advantage of potential changes in the marketplace that will have happened before the end user even knows about it. 

For that reason, trading tools must provide data in real time, for knowledge is power and data is the new gold. Having access to real time data, if platforms like Uniswap and others want to succeed, is key.

Data accuracy on DEXs and CEXs

At the same time, because they are decentralized, they’re not obligated to provide this functionality. That creates an opportunity for third party tools to fill that niche. At the end of the day, since centralized exchanges are custodians of their own data, you have to trust that they are publishing accurate data. 

So data accuracy on DEXs is always there, timeliness is sometimes there, and there’s a heavy, heavy reliance on products such as The Graph which power vast swathes of the DeFi space. Yet, they are deployed on centralized services.

If there is downtime on Google Cloud Platform, for example, then there is a huge number of platforms and tools that just cease to work. When certain DeFi apps go down, it is noticeable that trade volumes fall.

This happened when Infura experienced down time in November. MetaMask runs on Infura, and so MetaMask wallets ceased working. Trade volume on Uniswap disappeared in an instant. 

These points of centralization are a risk to truly decentralized trading. As DeFi grows, addressing the centralization that still exists in crypto will be central to achieving the industry’s original goals of decentralizing finance, as well as ensuring the integrity of the data which informs the decisions.

NOTE: The views expressed here are those of the author’s and do not necessarily represent or reflect the views of BeInCrypto.

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In compliance with the Trust Project guidelines, this opinion article presents the author’s perspective and may not necessarily reflect the views of BeInCrypto. BeInCrypto remains committed to transparent reporting and upholding the highest standards of journalism. Readers are advised to verify information independently and consult with a professional before making decisions based on this content.  Please note that our Terms and ConditionsPrivacy Policy, and Disclaimers have been updated.

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CryptoShark
With a background in IT spanning Software Engineering, Business Analysis and Intelligence and Infrastructure Architecture, CryptoShark first found the Cryptocurrency space through mining Ethereum from a spare gaming computer and later developed the popular decentralized charting platform, ChartEx. Working in the FinTech industry, it wasn’t long before he started applying his analytical skills, coupled with a software engineering background to build tools to analyse trading data from...
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