Intro
Have you ever wondered what blockchain analytics is and what there is to analyze on the blockchain?
It is not always clear what we call blockchain analytics. People in blockchain come up with new technologies, protocols, and use cases weekly. The problems and questions are still evolving.
For this reason, you better understand blockchain analytics by having a high-level overview describing its main components and use cases.
This article gives you an introduction to blockchain analytics. It shows what blockchain analytics is, how it relates to data analytics, and lists its main use cases and the platforms where people can analyze blockchains.
It answers the following questions:
- What is blockchain analytics, and how does it relate to data analytics?
- What is the difference between on-chain and off-chain analytics?
- What are the main use cases of blockchain analytics?
- What are the main blockchain analytics platforms?
What Is Blockchain Analytics
Blockchain analytics, or blockchain analysis, analyzes blockchain data to generate value from it. The term ‘blockchain analytics’ refers to different things as a forming topic.
Here is a list of common activities falling under ‘blockchain analytics’:
- Analyzing blockchain data for insights
- Investigating blockchain protocols, network, and governance mechanisms
- Using off-chain data to identify, match, and deduct on-chain information
- Inspecting and analyzing the wider ecosystem of a blockchain network (e.g., economics, community, media)
Blockchain analytics overlaps with data analytics at many points, but their relationship is unclear. The next section clarifies this.
What Is The Difference Between Blockchain Analytics and Data Analytics?
Blockchain analytics focuses on the blockchain, its subject domain. Data analytics refers to methods that use data to generate insights.
Data analysis is an important part of blockchain analytics, as data is a core component of every blockchain.
Bitcoin Data Structure. (source)
We can refer specifically to the data analysis part of blockchain by the term ‘blockchain data analytics’. However, people rarely make this difference and interchangeably use the terms ‘blockchain analytics’ and ‘blockchain data analytics’.
What is Blockchain Data Analytics
Blockchain data analytics addresses blockchain-related problems and produces insights, models, and data products using data analytics and data science methods.
Many of its methods are similar to data analysis, like time series and graph analysis.
However, blockchain data analysis differs from ’traditional’ data analytics in at least the following three aspects:
- Analysts often rely on blockchain data providers and platforms for data access.
- Blockchain data has special characteristics like immutability and pseudo-anonymity that influence analytical methods’ applicability and value.
- Blockchain projects often face analytic challenges specific only to them, like validation, transparent but anonymous transaction processing, and decentralized permission management.
Is All Blockchain Analytics Data Analytics?
Blockchain analytics goes beyond data analytics and uses many non-data analysis techniques.
Examples of non-data-related techniques are studying protocols and smart contract documentation, using secondary sources, and interviewing blockchain developers and users.
On-Chain and Off-Chain Analytics
People often distinguish on-chain and off-chain analytics:
What Is On-Chain Analytics
‘On-chain analytics’ refers to data analysis done on blockchain data.
On-chain data resides on the blockchain or originates in it, and on-chain data analytics is the process of analyzing it. It requires knowledge of data analytics, blockchain protocols, and the data structure of the blockchain.
Because of the structure of blockchain data, on-chain data analysis often focuses on the following data entities:
- Addresses: entities engaging in transactions on the blockchains
- Transactions: events representing messages and value transfer between the addresses
- Tokens: tradable assets or utilities residing on the blockchain
- Smart contracts: programs or protocols running on the blockchain
What is Off-chain Analytics
‘Off-chain analytics’ is any analysis relying on information outside the blockchain.
It has special importance in blockchain analytics because of the pseudo-anonymity of blockchain addresses. External observers can see the addresses on a public blockchain but cannot connect them to ‘real-world’ entities. Off-chain analytics uses data outside the blockchain and algorithmic methods to make this possible.
Off-chain analytics entails data (e.g., data from social media) and non-data analytic methods (e.g., qualitative ‘investigative’ practices).
Blockchain Analytics Use Cases
We can group blockchain analytics use cases based on the activity involved and the area where people use it. The following table summarizes the most common ones:
| Activity | Use Case | Area |
|---|---|---|
| Transaction & Entity Tracking | Track the history of funds, digital objects (e.g., documents, identities, personal records), and transactions. | Law Enforcement & Anti-Money Laundering, Blockchain Forensics, Regulation & Compliance, Supply Chain Analytics, Security & Identity Management |
| Organization / Network Analysis | Understand components and processes of blockchain projects (e.g., cryptocurrency & digital asset markets, DAOs, IoT networks, identity management services) and conduct due diligence on them to mitigate financial and security risk. | Blockchain & DAO Operations, Investment Research, Governance & Regulation, Hardware & Manufacturing |
| Opportunity Discovery | Identify new financial assets and opportunities to produce value. | Financial Trading, Business Strategy & Development |
| Real-Time Analytics | Monitor special events and create alerts. | Blockchain & DAO Development, System & Infrastructure Development, Network Engineering, Hardware Engineering, Finance, Manufacturing, Software Development, Economic Policy |
This list is still evolving as people in blockchain develop new solutions and uses cases.
Blockchain Analytics Tools & Platforms
Blockchain analytics tools and platforms help blockchain analysts to explore and investigate blockchain data.
Blockchain analysts often don’t have the skills and resources to access blockchain data directly. They rely on open-source and commercial platforms that serve the data in a more digestible format, like SQL.
The profile of these platforms depends on the problems they address and their customer base. There are blockchain analytic platforms specialized in forensics, trading, investment, security, and infrastructure. Platforms can be open-source, freemium, or purely fee-based.
The following table summarizes the main blockchain analytics tools and platforms.
| Type | Funcionality | Examples |
|---|---|---|
| Block explorers | Exploring individual addresses and blocks on the blockchain | Etherscan, Blockchain.com, Blockchair, Blockstream |
| On-chain query platforms | Providing a platform to analyze blockchain data in a query language, like SQL | Dune Analytics, Flipside Crypto, The Graph, Google BigQuery |
| Forensics and Anti-Money Laundering | Analyzing addresses and transactions to reveal illicit activity as part of blockchain forensics | Chainalysis, Elliptic, TRM Labs |
| Investment research | Providing on-chain and off-chain information for investors and traders | Nansen, Messari, Glassnode, Footprint Analytics |
| Security | Providing security and financial risk information of blockchain projects | CertiK, Valid Network |
Do You Want to Learn More About Blockchain Analytics?
This article gave a high-level overview of blockchain analytics, its types, and its relationship to data analytics. It also listed its main use cases and the most important tool and platforms.
I hope it helped you better understand blockchain analytics and where you can use it.
Do you have more questions about blockchain analytics? Do you miss something from the article? Let me know!