Enterprise Use of Quick -- Large Dataset Support

Q&A
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1

Hi AWS Community,

I’m exploring Quick for enterprise use and have two main questions so far : ) :

Question 1: Large Dataset Support Scenarios seem still limited to ~1M rows. For my enterprise needs at least LLM that can deal with (50M-100M+ rows):

  • Are there other Quick capabilities that handle bigger datasets?
  • Any workarounds or best practices for large data analysis?

Question 2: QuickSight Updates in Quick

  • Has QuickSight in Quick added new visuals/features beyond legacy QuickSight?
  • Or is it mainly the same QuickSight with new AI/agent capabilities?

Looking forward to your insights for our enterprise evaluation.

Thanks in advance !

Wei Ling

2

Hello WeilingP,

best on my understanding, i will try to answer to your questions , other experts as welcome to advice as well

Question 1:

→ with Current Scenario in Quicksight

  • You can add up to 10 data sources to a scenario.

  • Up to 20 visuals can be selected from a dashboard at a time.

  • Uploaded files must be in .xlsx or .csv format and can’t exceed 1 GB.

  • Data sources can have up to 200 columns

Question 2: QuickSight Updates in Quick → No Quick does not bring in new visuals type. Quick is the top of the umbrella where QuickSight is the BI component which has the visual types. other new capabilities includes below

  • Amazon Quick Flows: Automation feature that enables you to create intelligent workflows combining AI reasoning with business actions across multiple systems without programming knowledge

  • Amazon Quick Automate: Process optimization capabilities that streamline routine tasks and workflows

  • Amazon Quick Research: AI-powered autonomous agent that combines organizational data with web search to deliver expert-level research reports with verified sources and citations

  • Amazon Quick Index: Data discovery service that helps you find and understand your organization’s data assets

  • Custom chat agents: Specialized AI assistants that use your organizational data that you can build and customize

  • Spaces: Allow you to create custom knowledge bases that organize documents and dashboards with controlled access permissions for specific business contexts, including file uploads, dashboards, knowledge bases, topics, and actions

  • Actions: Enable you to connect third-party applications and your own APIs to Amazon Quick for workflow automation and reduced context switching

  • Knowledge bases: Enterprise-scale document management that connects to data sources like Amazon Simple Storage Service (Amazon S3) to automatically index and search large document collections

  • Extensions: Platform integrations like Slack that bring Quick insights and actions directly into conversational workflows where teams already collaborate

For Question 1 with large data set may be you could use knowledge base but again it will be like LLM answering to your prompt not sure if scenario kinda of response you may get.

Hope this gives some idea.

Cheers,

Deep

3 Likes
3

How is about the number of rows?
Still being limited to a maximum of 1 Million rows in Scenario?
Thanks in advance for your reply!