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Blockchain Data Analytics: A Scoping Literature Review and Directions for Future Research

Marcel Bühlmann, Hans-Georg Fill, Simon Curty

TL;DR

The paper conducts a scoping literature review to map the breadth of blockchain data analytics from 2008 to 2024, identifying six topic clusters and evaluating publication venues, institutions, and temporal trends. It employs a multi-step search protocol across major databases plus backward-forward searching, ultimately analyzing 466 primary studies after filtering. The core contributions include a taxonomy of six topics (illegal activity detection, data management, financial analysis, user analysis, community detection, mining analysis), insights into data sources and methods (notably graph analysis and ML for on-chain data), and a discussion of gaps—particularly the lack of organizational BI integration and holistic cross-domain frameworks. The study provides a structured foundation for future work by highlighting research gaps, suggesting directions for integrating on-chain/off-chain data, and emphasizing enterprise-oriented analytics and KPI-based evaluation.

Abstract

Blockchain technology has rapidly expanded beyond its original use in cryptocurrencies to a broad range of applications, creating vast amounts of immutable, decentralized data. As blockchain adoption grows, so does the need for advanced data analytics techniques to extract insights for business intelligence, fraud detection, financial analysis and many more. While previous research has examined specific aspects of blockchain data analytics, such as transaction patterns, illegal activity detection, and data management, there remains a lack of comprehensive reviews that explore the full scope of blockchain data analytics. This study addresses this gap through a scoping literature review, systematically mapping the existing research landscape, identifying key topics, and highlighting emerging trends. Using established methodologies for literature reviews, we analyze 466 publications, clustering them into six major research themes: illegal activity detection, data management, financial analysis, user analysis, community detection, and mining analysis. Our findings reveal a strong focus on detecting illicit activities and financial applications, while holistic business intelligence use cases remain underexplored. This review provides a structured overview of blockchain data analytics, identifying research gaps and proposing future directions to enhance the fields impact.

Blockchain Data Analytics: A Scoping Literature Review and Directions for Future Research

TL;DR

The paper conducts a scoping literature review to map the breadth of blockchain data analytics from 2008 to 2024, identifying six topic clusters and evaluating publication venues, institutions, and temporal trends. It employs a multi-step search protocol across major databases plus backward-forward searching, ultimately analyzing 466 primary studies after filtering. The core contributions include a taxonomy of six topics (illegal activity detection, data management, financial analysis, user analysis, community detection, mining analysis), insights into data sources and methods (notably graph analysis and ML for on-chain data), and a discussion of gaps—particularly the lack of organizational BI integration and holistic cross-domain frameworks. The study provides a structured foundation for future work by highlighting research gaps, suggesting directions for integrating on-chain/off-chain data, and emphasizing enterprise-oriented analytics and KPI-based evaluation.

Abstract

Blockchain technology has rapidly expanded beyond its original use in cryptocurrencies to a broad range of applications, creating vast amounts of immutable, decentralized data. As blockchain adoption grows, so does the need for advanced data analytics techniques to extract insights for business intelligence, fraud detection, financial analysis and many more. While previous research has examined specific aspects of blockchain data analytics, such as transaction patterns, illegal activity detection, and data management, there remains a lack of comprehensive reviews that explore the full scope of blockchain data analytics. This study addresses this gap through a scoping literature review, systematically mapping the existing research landscape, identifying key topics, and highlighting emerging trends. Using established methodologies for literature reviews, we analyze 466 publications, clustering them into six major research themes: illegal activity detection, data management, financial analysis, user analysis, community detection, and mining analysis. Our findings reveal a strong focus on detecting illicit activities and financial applications, while holistic business intelligence use cases remain underexplored. This review provides a structured overview of blockchain data analytics, identifying research gaps and proposing future directions to enhance the fields impact.
Paper Structure (13 sections, 3 figures, 10 tables)

This paper contains 13 sections, 3 figures, 10 tables.

Table of Contents

  1. Introduction
  2. Related Work on Blockchain Data Analytics
  3. Applied Search Protocol and Review Process
  4. Descriptive Analysis Results of the Systematic Literature Review Process
  5. Content Based Analysis - Major Topics in Blockchain Data Analytics
  6. Illegal Activity Analysis
  7. Data Management
  8. Financial Analysis
  9. User Analysis
  10. Community Detection
  11. Mining Analysis
  12. Discussion Results and Future Challenges
  13. Conclusion

Figures (3)

  • Figure 1: The diagram of the applied systematic literature search, retrieval and review process with individual activities and number of publications per step. The literature retrieval process is supplemented with the metadata-retrieval and metadata normalization in a relational database.
  • Figure 2: The diagram of the applied literature coding and iterative topic clustering process with the dataset size n=466.
  • Figure 3: The evolution of the number of publications published per topic cluster derived during the literature review process and the total number of papers published per year between 2011 and the beginning of 2024 with n=466. The average exchange price (USD) of Bitcoin is added for referencing public awareness for blockchain, which might influence the number of papers published.