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Amazon Quick Sight enables multi-dataset relationships for flexible data modeling

By PulseAugur Editorial · [2 sources] ·

Amazon Quick Sight has introduced a new feature called Multi-Dataset Relationships, allowing users to define logical connections between different datasets. This eliminates the need for upfront data flattening, enabling runtime joins that preserve native data granularity and simplify data management. The feature supports various data modeling patterns like star, snowflake, and constellation schemas, offering greater flexibility for complex analytical scenarios. AI

IMPACT Simplifies data preparation for AI/ML analytics by allowing complex data relationships to be managed within the BI tool.

RANK_REASON Product feature release for a business intelligence tool.

Read on AWS Machine Learning Blog →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Amazon Quick Sight enables multi-dataset relationships for flexible data modeling

COVERAGE [2]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Ying Wang ·

    Data modeling best practices for Amazon Quick Sight multi-dataset relationships

    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 …

  2. AWS Machine Learning Blog TIER_1 English(EN) · Ying Wang ·

    Data modeling patterns for Amazon Quick Sight multi-dataset relationships

    In this post, we shift from concepts to patterns. For each schema, you’ll find a table structure, use cases, implementation steps, and sample SQL queries. We also cover workarounds for advanced scenarios that require extra modeling steps, and close with a summary of current limit…

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