Embedded analytics involves integrating data analytics and visualization capabilities directly into a user's workflow, enhancing user experience by eliminating the need for manual data processing in separate tools. This practice is becoming essential as employees reportedly spend significant time switching between applications to gather information. A modern embedded analytics stack typically includes a data source, a semantic layer, and a presentation layer, with the semantic layer playing a critical role in defining metrics, governing data access, and caching information for consistent performance. Tools like Cube, Snowflake, and Databricks exemplify components of this stack, offering scalable and efficient data solutions. For presentation layers, options range from traditional BI tools like Tableau and Power BI to more flexible interactive notebooks such as Hex and Deepnote, as well as customer-facing frameworks like React and D3.js. These tools enable the creation of tailored, native analytics experiences that are both flexible and efficient, illustrating a significant advancement from traditional BI approaches.