What is blockchain data analytics, and why should you use it in your business?

Blockchain data analytics has become a better option for businesses to analyze their data on blockchain for better data security and efficiency.

But what are the other benefits of blockchain data analytics? Let’s check in detail about blockchain data analytics, how it works, and the methods to analyze data on the blockchain.

What is blockchain data analytics?

Blockchain data analytics is the process of analyzing data on a blockchain. The process involves inspecting, identifying, understanding, and visualizing data on a blockchain. The analytics help users to understand the various aspects of that specific blockchain network.

Blockchain analytics helps improve the security of the blockchain network from unwanted transactions such as money laundering and other kinds of online frauds.

How does blockchain data analytics work?

Blockchain analytics help extract and process data into easily readable formats. Ethereum ETL is an open-source project allowing users to convert blockchain data into readable formats such as CSV.

The most common objective of using blockchain data analytics is to track each transaction on their network. Blockchain analytics tracks the crypto wallets of each user for tracking all the transactions. A readable data format helps companies analyze suspicious transactions in their networks.  

Each crypto wallet has its unique address that acts as a unique identifier through which the blockchain data analytics tracks each user’s transaction. The business can easily find out to suspicious users through their wallet addresses with the help of blockchain analytics, so the companies can make their networks more secure.

Know how blockchain and data science relates to each other for understanding their work in depth.     

Relation between Blockchain and Data Science

You can understand the relation between blockchain and data science by knowing them separately.

What is blockchain?

Blockchain is a decentralized and irreversible virtualized data record that tracks crypto transactions and other digital assets across the internet. The assets include patents, trademarks, smart contracts, indirect commodities, etc. The multiple computers are connected across a blockchain network, providing shared computing power and data storage. 

What is data science?

In data science, we extract knowledge and information from organized and unorganized data with the help of machine learning, artificial intelligence, and other advanced data science methods. Data science helps companies and organizations know the outcomes from their previous data records to make better decisions.

Now, let’s check how blockchain and big data differ.

The Main difference between blockchain and data science

The following given parameters help you better differentiate between blockchain and data science.

BlockchainData Science
WorkingData recording and validation. Data analytics.
Aim To allow data to be recorded and distributed immutably. To construct the methods for data extraction.
UsesReal-time transactions. Gives in-depth data analysis. 
Benefits Maintain users’ safety, networks speed, etc.Enhances data efficiency. 
PurposeMaintain Data integrityAccurate data prediction

Now, let’s understand why blockchain data analytics is important.

Why are blockchain analytics important?

Blockchain analytics provides transparency in crypto transactions within blockchains. Many companies who involve the use of blockchain in their business perform blockchain data analytics to make their network more secure.

Also, using blockchain with data science helps companies perform better data operations and analyze their data for better business results. Know how to perform blockchain analytics.

How do you analyze data on the blockchain?

There are many ways to analyze the data on the blockchain, and each method requires three general steps of blockchain analysis. 

The first is address classification, in which we connect the location address to real-world entities. 

Next, we check the transaction risk score among the blockchain connections between the entities. 

The third step is an investigation where we use data visualization tools to represent newly organized blockchain data. Let’s check the steps to efficiently showcase graphical representations of blockchain data:

1. Data filtering

The data involved in blockchain data analytics is big and expanding rapidly. You will need to filter data based on your preferred attribute, such as transaction size, wallet ID, risk score, transaction times, etc.

With data filtering, the automatic layout is another best way to help investigators and analysts investigate big and complex blockchain data.

2. Data grouping 

The process involves creating a new address for each transaction across multiple wallets. The grouping will help insurance to reduce the risk of fund theft. There is a need for investigators to combine different wallet addresses for data grouping manually.

3. Enabling users driven capabilities

After extracting data from the blockchain, the analyst can represent that data to the user with custom graphics styling. Describing data in a customized way allows users to analyze and understand the blockchain data more efficiently.

Implement the “land and expand” data visualization approach so the users can easily access a large amount of data.

4. Smooth animation

Integrating the smooth animation will help you maintain the users’ interest. Smooth animation enables a great accessing experience for users to read the blockchain analytics report.

5. Make data easier to export

Along with allowing users to read the blockchain data from the software efficiently, it can be better to allow them to export data into other formats, such as PDF reports and image files. Allowing users to export data will helps them to have instant access to the visualized data and will provide an easier way to share it with anyone. 

6. Graphics rendering of data

Accessing blockchain data in a large amount requires powerful graphics rendering, so the data loads quickly on their screen. You can integrate high-performing graphical renderers like WebGL, SVG, and other more straightforward visual rendering approaches.  

Knowing the different use cases of blockchain data analytics will help you understand why you should use the same in your business.

Different use cases of blockchain data analytics

Understand different ways how businesses are using blockchain analytics. 

1. Identify High-Risk Customers

Blockchain companies can identify their customers involved in criminal activities by tracking their crypto transactions.

Blockchain data analytics helps companies screen wallets to discover suspicious or illegal transactions on their networks. Eliminating such suspicious customers from their network helps them manage their good reputation in the market to maintain their users’ trust. 

2. Business expansion in other regions

Blockchain companies can identify their customers involved in criminal activities by tracking their crypto transactions.

Blockchain analytics helps companies screen wallets to discover suspicious or illegal transactions on their networks. Eliminating such suspicious customers from their network helps them manage their good reputation in the market to maintain their users’ trust. 

3. Helps business to keep their data safe from competitors

Companies are now storing their data on blockchain networks to protect them from competitors. Companies perform blockchain data analytics to eliminate the risk of having any security threat in blockchain networks. So they can gain an overall insight and transparency in their blockchain-related networks.

4. Improving data sharing management

Blockchain provides easy accessibility of their data storage to the users. With blockchain analytics, the companies can distribute their data easily to their different teams to work on and manage the separate data efficiently.  

5. Helps in making better business decisions    

Companies are now storing their data on blockchain networks to protect them from competitors. Companies perform blockchain data analytics to eliminate the risk of having any security threat in blockchain networks. So they can gain an overall insight and transparency into their blockchain-related networks.

6. Enable real-time analysis

Without blockchain, it is difficult for companies to analyze real-time data. To identify any data irregularities in the early stages, the company prefers using blockchain technology in data science to take full advantage of real-time data analysis.

7. Improves data accuracy

As the blockchain stores data in private and public nodes,  the company can examine and cross-check its data at the entry point to validate its accuracy before adding data to other blocks. 

8. Prevents data duplication

Blocks and restricts data duplications due to their irreversible nature. Avoiding data replications helps companies to improve the accuracy of the data. 

Blockchain analytics verify and cross-check the data at every block with multiple signatures on blockchain records and doesn’t grant data access until the exact signature match has been found. 

How is blockchain analytics helping businesses? 

Due to the decentralized nature of blockchain, businesses are implementing blockchain technology on their data records by hiring blockchain developers. Using blockchain analytics on a large scale opens new opportunities for entrepreneurs to help them starting their blockchain analytics companies. 

Also, using blockchain technology for data analytics is economical as it provides data storage and computing capabilities at a low cost compared to technology based on centralization. 

There is a great demand for blockchain analytics in multiple sectors to secure their data and make better predictive analytics models for better future decisions such as

  • Healthcare 
  • Insurance
  • Automotive
  • Media and entertainment
  • Telecommunications
  • Retail and consumer goods

How can Idea Usher help?

Combining blockchain with data analytics is a good step toward your business’s success. Even more, along with working with data analytics, blockchain has considerable future potential. 

In case you think there is a need to integrate blockchain technology into your business or want to build blockchain-based digital products, you can contact Idea Usher.  

Idea Usher is a team of data engineers and blockchain developers. Their team can help you build and market your blockchain products.

Contact us:

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(+1)732 962 4560

(+91)859 140 7140

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FAQ

1. Can data analytics be used with blockchain?

Businesses can use Data analytics with blockchain for analyzing, identifying, and visualizing data on the blockchain.

2. How do you analyze data on the blockchain?

In three steps, we can analyze data on the blockchain: 

I. Data classification on different parameters

II. Checking transaction risk score between entitles

III. Data investigation using data visualization tools

3. What is a blockchain data analyst?

Blockchain analyst examines the data, and their usage shows the analyst can identify the areas of improvement for improving data efficiency and security in blockchain.

4. Can blockchain handle big data?

Blockchain has a great potential to perform big data analytics due to its decentralized nature. The blockchain helps big data to

  • Organize raw data
  • Improve the security and privacy of big data
  • Upgrade the quality of data sharing and management, etc.
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