Embedded analytics is the integration of data analysis capabilities directly into the applications that teams already use, enabling users to explore data and generate insights without switching tools. This method improves efficiency by providing real-time metrics within operational tools, allowing for immediate decision-making and reducing dependency on separate BI tools. There are various types of embedded analytics, including internal, customer-facing, and partner or portal embedded analytics, each influencing security, customization, and scalability. Under the hood, embedded analytics involves authentication, semantic layers, query optimization, and multi-tenant security to ensure seamless and secure data access. The emergence of AI-native platforms, like Hex, is transforming embedded analytics by integrating AI deeply into their architecture, allowing for a better understanding of data models, security rules, and metric definitions, which facilitates more efficient collaboration and data exploration.