SPSS by IBM
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DragonGlass is a cloud-based data service that provides access to live and historical transactional data across the Hedera Hashgraph distributed ledger network. It acts as a data aggregation and analytics platform, offering APIs and tools for developers and businesses to query, monitor, and analyze network activity, token transactions, smart contract executions, and account information. By structuring and serving the vast stream of public ledger data, it enables users to build applications, conduct audits, perform market analysis, and gain insights into the dynamics of the Hedera ecosystem without needing to directly operate a network node. This service is designed for blockchain developers, businesses building on Hedera, financial analysts, auditors...
This service is designed for blockchain developers, businesses building on Hedera, financial analysts, auditors, and researchers interested in the Hedera Hashgraph network. It is ideal for anyone who needs reliable, queryable access to comprehensive and real-time data from this public distributed ledger to inform development, investment, or research decisions.
Our verdict is that DragonGlass is a critical infrastructure service for the Hedera ecosystem, effectively bridging the gap between raw ledger data and actionable information. Its cloud-based delivery of live and historical data makes it an invaluable tool for developers and analysts operating in this specific blockchain environment.
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This service is designed for blockchain developers, businesses building on Hedera, financial analysts, auditors, and researchers interested in the Hedera Hashgraph network. It is ideal for anyone who needs reliable, queryable access to comprehensive and real-time data from this public distributed ledger to inform development, investment, or research decisions.
These are common features buyers compare in Statistical Analysis Software. Product-specific availability should be confirmed with the vendor.
A rule-based machine learning approach to uncover significant relationships between variables in extensive datasets.
A statistical procedure that uses an observed distribution to estimate parameters of an underlying distribution.
The use of visual elements like charts and graphs to represent complex data sets.
Predict future outcomes using historical data and current market trends.
Involves the analysis of data sets containing multiple variables.
Utilize historical data trends to forecast future outcomes and behaviors.
An analytical method to determine the relationship between independent and dependent variables.
Monitor and analyze numerical metrics and performance data through visual reports.
Utilizes statistical methodologies to aid in and uphold process quality control.
Evaluates a method's performance by drawing a random sample from a normal distribution.
Analyzes the anticipated timeframe leading up to the occurrence of one or multiple events.
A sequence of data points arranged chronologically.
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