Business intelligence analysts routinely face the same challenge at the start of every analytics project: the data needed to answer a single business question lives across multiple tables. Sales transactions sit in one place, customer demographics and product attributes in another, while returns, forecasts, and operational metrics occupy still others.

Until now, combining these tables in Amazon Quick Sight required pre-joining everything into wide, denormalized datasets before any analysis could begin. That approach works. But it forces data-modeling decisions up front, duplicates measures across different grains, introduces maintenance overhead, and typically produces a different dataset for almost every reporting scenario.

Today, we are excited to announce Multi-Dataset Relationships in Amazon Quick Sight. This new capability lets you define logical relationships between Quick Sight datasets and perform runtime joins at query time. Instead of flattening tables ahead of time, you keep each table as its own Quick Sight dataset and declare how those datasets relate to one another inside a Quick Sight Topic. Quick Sight then assembles precisely the join it needs for visuals, calculated fields, filters, or natural-language Q&A.