Data Analytics — The Next Breakout Area of the Crypto Space

The crypto market is experiencing a boom currently. The rally of bitcoin and the success of new cryptocurrencies help to attract the attention of the world community to this area. At the same time, the blockchain infrastructure is also developing, including one aimed at the interaction of different blockchain ecosystems.
And the data and the work on its analysis come to the fore.

Data analytics is a promising new area in the cryptosphere

There are many types of data in the cryptosphere - some of them are important for analysis, some of them can be neglected. Today, data is everywhere in the blockchain world - from the education level of specialists working on a token to the weighted average cost of a specific token per year.

Of course, it is also important to take into account the specifics of the request - for what purposes do you want to analyze the data? Determine how popular the cryptocurrency is or, for example, at what average price Ben Mauro's NFT cards are sold. Multitasking and extensive practical applications of data analysis have led to its development at the present stage. Let's see what kind of crypto data can be analyzed)

It is best to use special API to analyze on-chain data. The main types of data for such analysis include:

1. The value of the wallet's assets and its historical dynamics, as well as the presence of certain tokens on the wallet and their dynamics. For example, you are interested in where a well-known cryptocurrency fund invests or you want to find out how successful were the past operations with the purchase and sale of tokens - using the API and blockchain data, all this information is in the palm of your hand.

2. The ratio of the number of active addresses in the network of a particular blockchain in relation to inactive ones, as well as their total number. This metric allows us to assess how much a given blockchain network is currently being used. Using a comparison of the data of a certain network with another, we can conclude about the level of implementation of both networks)

3. Farming data and DEX analysis. How much profit did the whale get, which farm it threw it this time, which blockchain network big wallets prefer to farm, and so on)

4. Staking and hashrate data. Analysis of the hashrate in projects with PoW consensus helps to mark the demand and activity of miners at the moment and not only) Studying the data of large validators in projects with Proof-of-stake consensus helps to determine, for example, your chances for producing a block.

5. Trading volume and liquidity. High liquidity is good, which means this cryptocurrency has many buyers and sellers, users are interested in it, in one way or another. Low liquidity implies some difficulty in buying a token at a certain price. Trading volume can also be used as an indirect indicator of the demand for a coin.

There are many indicators for data analysis - and, first of all, their interpretation is important, what conclusions can you draw from these data and how correct they are. It is good to analyze the data not separately for each indicator, but to consider the whole system as a whole.

Currently, Covalent API is the one of the most user-friendly systems, but at the same time with a huge range of capabilities. It is quite easy to use, and, unlike GraphQL, even a user with basic skills can quickly figure it out and start submitting their requests.

Inteface of Covalent API

You can get acquainted in more detail with the platform's functionality by following these links:
https://www.covalenthq.com/docs/
https://www.covalenthq.com/docs/api

The possibilities of API Covalent are truly endless - the system already supports 8 different blockchain networks, and indexes 50+ projects. Many different features are also available, including:

  • Tracking transactions
  • Wallet balance tracking and its history
  • NFT Tracking
  • Contract metadata
  • And many others

To summarize, the demand for data analysis in the crypto world will only grow. There will be new types of data, new projects, new users... And data analysis platforms such as Covalent will help us deal with all this.

To learn more about Covalent visit covalenthq.com
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