Bring structured and unstructured data together with Amazon Quick

Organizations collect data in many forms. Structured data lives in databases and spreadsheets, whereas unstructured data sits in documents, reports, and files stored across file systems. Analyzing both together typically requires switching between multiple tools, running separate queries, and manually correlating results.

Amazon Quick addresses this with a unified experience. You can connect structured data through enriched datasets and unstructured data through S3-backed knowledge bases . You can then query both through a single conversational AI agent.

The following diagram illustrates how each component connects to deliver a unified data experience through Amazon Quick.

Figure 1: Solution architecture for combining structured and unstructured data in Amazon Quick

When you ask a question about structured data, the agent uses text-to-SQL to translate your natural language into a SQL query. It runs the query against the dataset and returns the results in a readable format. This means you can ask complex analytical questions without writing SQL yourself.

With this layered approach, you can expand the solution over time. When you add a new data source to the Space, the agent linked to that Space can use it, and responses respect the permissions of the user who asks.

Unstructured documents: Upload these to your Amazon S3 bucket for the knowledge base:

Structured data: Download this file to your computer. You upload it directly to Amazon Quick in Step 3: