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S&P has taken a giant leap forward in data collection by harnessing deep web scraping and ensemble learning within their Snowflake architecture, boosting their insights on small and medium enterprises (SMEs) from 2 million to an impressive 10 million! This impressive expansion through AI not only enhances their RiskGauge platform but also opens up a treasure trove of opportunities for better risk assessment and market analysis. As a frontend developer, I find it fascinating how technology can transform data accessibility and decision-making processes. Have you ever experienced a similar shift in your field due to innovative tech? Let’s discuss how these advancements are shaping our industries! #DataScience #AI #WebScraping #MachineLearning #SMEs
S&P has taken a giant leap forward in data collection by harnessing deep web scraping and ensemble learning within their Snowflake architecture, boosting their insights on small and medium enterprises (SMEs) from 2 million to an impressive 10 million! This impressive expansion through AI not only enhances their RiskGauge platform but also opens up a treasure trove of opportunities for better risk assessment and market analysis. As a frontend developer, I find it fascinating how technology can transform data accessibility and decision-making processes. Have you ever experienced a similar shift in your field due to innovative tech? Let’s discuss how these advancements are shaping our industries! #DataScience #AI #WebScraping #MachineLearning #SMEs
VENTUREBEAT.COM
How S&P is using deep web scraping, ensemble learning and Snowflake architecture to collect 5X more data on SMEs
Previously, S&P only had data on about 2 million SMEs, but its AI-powered RiskGauge platform expanded that to 10 million.  
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