Analytics Platform
Analytics
Analytics is the premier visualization toolkit for Decentralized Identity, helping uncover hidden relationships between trust-chains, tracing historic records, and comparing and validating claims to their root of trust. Find similarities and detect unusual patterns through linked-data analysis, with findings presented in an easily understandable graph. The intuitive interface allows professionals to navigate the complex web of decentralized identity with unprecedented clarity. The platform offers seamless data integration capabilities, allowing you to ingest your own SSI-related data through a user-friendly API for further processing, either immediately or at a later time. This feature empowers you to keep track of, manage, and filter your collected data efficiently. When you're ready for an in-depth analysis, easily transition to our comprehensive graph view for a deeper understanding of your decentralized identity ecosystem. With analytics, you have complete control over your data journey:
Data Ingestion: Effortlessly import your SSI-related data via our intuitive API.
Data Management: Organize, filter, and maintain your collected information with ease.
Advanced Analysis: Dive into detailed graph-based visualizations when you need deeper insights.
Statistics
With Statistics, you can better understand activity on selected VDRs, make informed business decisions, and follow trends. Narrow down interesting datasets to later analyze them in more detail with an analytics graph view. Blocktrust Analytics is currently the only provider with insights into the DID PRISM method and up-to-date views on all major INDY networks, making it an invaluable resource for professionals in the decentralized identity space. Our statistics module offers additional powerful features:
Real-time Operation Tracking: Directly select newly created operations on different networks, filter based on various criteria, and mark the data for further analysis.
DID Resolution and History: Resolve DIDs to their DID-Documents, including access to historic versions. Follow the changes chronologically to gain a comprehensive understanding of DID evolution.