The Modern Data Stack for Embedded Analytics

The concept of embedded analytics refers to bringing rich data experiences to users within their natural workflow, without the need to toggle between applications. This technology has gained significant traction, driven by the rise of cloud data warehouses and advancements in front-end development tools. The modern data consumer is becoming increasingly diverse, with less technical expertise and varying expectations for usability, richness, and responsiveness. To meet these demands, companies are building customizable and performant embedded analytics features using modern front-end tools, such as React, Hex, Observable, and Streamlit. A cloud data warehouse-centric architecture is emerging, where the data warehouse serves as a backend for data analytics applications, including embedded analytics. This architecture simplifies security and streamlines software onboarding. The semantic layer plays a crucial role in supporting embedded analytics, requiring first-class support for cloud data warehouses, advanced caching, data modeling, diverse APIs, and a hybrid presentation layer to cater to different data consumers, use cases, and teams.

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