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Blockchain Data Analytics: Review and Challenges

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arxiv 2503.09165 v2 pith:5P6HHYT2 submitted 2025-03-12 cs.CR cs.DB

classification cs.CRcs.DB
keywords dataanalyticsblockchainacademicindustryresearchchallengesliterature
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The integration of blockchain technology with data analytics is essential for extracting insights in the cryptocurrency space. Although academic literature on blockchain data analytics is limited, various industry solutions have emerged to address these needs. This paper provides a comprehensive literature review, drawing from both academic research and industry applications. We classify blockchain analytics tools into categories such as block explorers, on-chain data providers, research platforms, and crypto market data providers. Additionally, we discuss the challenges associated with blockchain data analytics, including data accessibility, scalability, accuracy, and interoperability. Our findings emphasize the importance of bridging academic research and industry innovations to advance blockchain data analytics.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. ManiScope: LLM-Assisted Visual Analytics of Cryptocurrency Manipulation Risk

    cs.HC 2026-07 conditional novelty 6.0 of 10

    An LLM co-analyst plus coordinated crypto views can reduce manual evidence-seeking and organize manipulation-risk findings around user hypotheses in a 12-person practitioner study.

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