Introduction

Transacting with and proving ownership of a digital asset on a blockchain requires the usage of NFTs, or non-fungible tokens. With the rise of NFTs, digital data such as movies, photographs, and artwork have become more popular (Non-Fiction Displays). NFT transactions have reached $2.5 billion as of now in 2021. The Atrium network was affected as a result of the popularity of the CryptoKitty project. Because of the Ethereum Blockchain's inadequacies, Dapper Labs, the creators of CryptoKitties, have created Flow blockchain in an effort to make it the best platform for NFT tokens.

Method

In the current dashboard I'll trying to find an explanations to following issues:

• Do times of high transaction volume lead to more transaction failures? Create a visualization that shows the relationship between transaction volume and success rate of transactions since May 9th.

• Are there any noticeable patterns to when transactions are more likely to fail? Were there specific events that seem to cause transaction failures?

And for this I use flow.core.fact_events table to calculate the number of failed transactions and volume of those, then compare it with all and successful transactions.

So let's to look at the findings.

Analysis

• The count of transactions per day is shown in the above chart that is distinguished by the types of all transactions: failed and successful transactions. (in hourly time frame)

• The volume of transactions per day is shown in the above chart that is distinguished by the types of all transactions: failed and successful transactions.  (in hourly time-frame and Log scale in Y axis)

Discord: 0xHaM☰d#8391

• In the last chart, the total of daily volume in the bar chart vs. the count of transactions in the line charts for the total number of transactions (the green color line), successful transactions (the purple color line), and failed transactions (the green color line) are shown.

Concluson

• As of the findings in this dashboard that are trying to investigate the relationship between the volume of transactions and failed transactions, we can't find a significant relationship between volume and failure with certainty in transactions in the time period since May 9th. But as well as the last chart, we can see that on the days that volume goes up to more than normal range, the number of failed transactions goes up more than normal range. This is observable on period time from May 22nd to 26th, when volume from 11.79M goes up to 2B, the number of failed transactions goes from 20k per day up to more than 239k per day and remained higher than the count of successful transactions. 

• The volume of transactions per day is shown in the above chart that is distinguished by the types of all transactions: failed and successful transactions.  (in daily time-frame and Log scale in Y axis)

• The count of transactions per day is shown in the above chart that is distinguished by the types of all transactions: failed and successful transactions. (in daily time frame)