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Generative BI with Quicksight

Generative BI with Quicksight

Join us for an in-depth exploration of Generative BI with Amazon Quicksight! In this Twitch stream, we'll dive into the latest advancements in business intelligence and data visualization, using Quicksight's powerful generative AI capabilities.

Tony Mullen
Amazon Employee
Published Jul 11, 2024
Here are the key points from the show:
  • QuickSight is Amazon's cloud-based business intelligence and data visualization service. It allows users to create interactive dashboards, generate paginated reports, and embed visualizations in applications.
  • QuickSight supports a wide range of data sources, including files, databases, SaaS applications, and more. Data can be cached in the Spice in-memory data store for performance.
  • Pricing is based on reader and author users, with different rates for fixed vs committed usage. There are also options for anonymous/embedded usage.
  • The demo showcased QuickSight's "Generative BI" features powered by Amazon Q, their natural language processing capability. This includes:
    • Executive summaries that automatically generate high-level insights from the data
    • The ability to ask questions in natural language to get visualizations and insights
    • Drill-down capabilities to understand drivers behind trends/anomalies
    • The option to give feedback on the generated insights
  • Creating calculated fields and new visualizations through natural language commands was demonstrated as a way to rapidly build out analyses.
  • The topic administration capabilities were highlighted, showing how administrators can see user questions, provide feedback, and tune the data model.
  • While forecasting was not shown in this demo, it was noted as another advanced analytics capability within QuickSight.
Check out the recording here:
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Hosts of the show 🎤

Tony Mullen - Senior RDS Specialist Solutions Architect @ AWS

Guests 🎤

Andrew Bacon - QuickSight Specialist Solutions Architect @ AWS

Links from today's episode

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.

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