How Faraday simplifies sentiment analysis and generates personalized content using BigQuery
Join Faraday’s CTO Seamus Abshere as he shares how we’re using Google Cloud’s BigQuery to transform our workflows with the new Large Language Model (LLM) capabilities.
Faraday has been pioneering the use of Google Cloud's BigQuery and with its recent addition of LLMs, we’ve unlocked even more powerful use-cases. In this video, Seamus dives into how LLMs are improving sentiment analysis, content generation, and streamlining our data processes—all within BigQuery, without needing complex infrastructure.
In this video, you’ll learn:
- How Faraday improves sentiment analysis accuracy with BigQuery LLM feature
- The benefits of generating personalized content directly within BigQuery
- How BigQuery’s LLM feature simplifies our workflows and data processes
Ben Rose
Ben Rose is a Growth Marketing Manager at Faraday, where he focuses on turning the company’s work with data and consumer behavior into clear stories and the systems that support them at scale. With a diverse background ranging from Theatrical and Architectural design to Art Direction, Ben brings a unique "design-thinking" approach to growth marketing. When he isn’t optimizing workflows or writing content, he’s likely composing electronic music or hiking in the back country.
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