Awesome GitHub RepositoriesEmbedded Analytics

Metabase is a business intelligence platform designed to connect to various storage systems and relational databases for data exploration, visualization, and reporting. It provides a centralized environment where users can build queries through a graphical interface or raw code, transforming raw information into interactive dashboards and charts. The platform is built to support self-service analytics, allowing non-technical team members to extract insights without requiring deep knowledge of database syntax. The platform distinguishes itself through a metadata-driven modeling layer that abst

DataEase is an open-source, self-hosted business intelligence platform designed for building interactive data visualizations and managing analytical reporting. It provides a centralized environment where users can construct dashboards through a drag-and-drop interface, connecting to diverse data sources including relational databases, data warehouses, and external APIs. The platform distinguishes itself through its focus on embedded analytics and enterprise-grade governance. It allows for the seamless integration of charts, dashboards, and management modules into third-party web applications

Cube is a semantic data layer that provides a unified framework for defining business metrics, dimensions, and relationships across diverse data sources. By acting as a headless business intelligence engine, it transforms raw data into a governed model that can be queried via SQL, REST, and GraphQL interfaces. This architecture ensures consistent data definitions and logic across all downstream analytical applications and reporting tools. The platform distinguishes itself through its integrated conversational AI capabilities, which allow users to explore data using natural language. It orches

Cube is a semantic layer data platform that maps raw SQL databases to standardized business metrics and dimensions. It functions as a SQL dialect translator, converting abstract semantic queries into optimized SQL statements for various cloud data warehouses. The platform operates as a multi-tenant data gateway, isolating information and security permissions for different customers within a single deployment. It includes a relational caching engine that stores pre-aggregated query results to reduce latency and decrease the load on primary data warehouses. The system provides a REST-based int

Pygwalker is a library that transforms tabular data into interactive, drag-and-drop interfaces for exploratory analysis and visualization. It functions as a grammar-based framework that translates user interactions into declarative chart definitions, allowing for the creation of dynamic data exploration environments directly within notebooks or embedded web applications. The system distinguishes itself by offloading heavy analytical computations to backend kernels, which maintains responsiveness when visualizing large datasets. It supports the serialization of visual states into portable conf

🔥 基于大模型和 RAG 的智能问数系统，对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.

Lightdash is an open-source business intelligence platform that treats analytics logic as code. It centralizes metric and dimension definitions in a semantic layer, allowing data teams to define business metrics in YAML files version-controlled alongside data models. This approach ensures consistent, governed data access without requiring users to write SQL. Lightdash introduces CI/CD workflows for BI content, enabling teams to validate, test, and deploy analytics changes through automated pipelines and isolated preview environments. Its natural language query interface allows users to ask qu

Visual Insights es una plataforma de análisis exploratorio de datos automatizado y herramienta de inferencia causal diseñada para descubrir patrones y relaciones de causa y efecto dentro de los datasets. Funciona como una librería de visualización de datos interactiva utilizando un enfoque de gramática de gráficos para generar gráficos y dashboards multidimensionales. El proyecto se distingue por una interfaz de lenguaje natural que traduce preguntas en texto plano a respuestas y visualizaciones de datos mediante un modelo de lenguaje. Proporciona un framework especializado para el descubrimiento e inferencia causal, permitiendo a los usuarios identificar enlaces entre variables mediante gráficos causales interactivos y realizar análisis de tipo "qué pasaría si" (what-if) para validar hipótesis. La plataforma cubre un amplio rango de capacidades, incluyendo limpieza visual de datos, perfilado estadístico y transformación automatizada de datasets. Soporta la integración de datos diversos desde archivos locales y bases de datos remotas, y cuenta con un motor de procesamiento de alto rendimiento para manejar grandes datasets localmente. Además, el sistema permite embeber componentes de análisis interactivos en aplicaciones web y notebooks.

Chartbrew is a self-hosted business intelligence platform and data visualization engine designed to transform raw data from SQL databases and external API endpoints into interactive charts and dashboards. It serves as a tool for building analytics dashboards that monitor business metrics and KPIs through a privately hosted environment. The platform distinguishes itself with an embedded analytics workflow, allowing users to generate secure, time-limited shared links and iframes to display private charts on external websites. It also provides programmatic chart generation via API and integrates

Just-dashboard es un framework de visualización de datos que permite la creación de paneles web interactivos a través de archivos de configuración declarativos. Al definir diseños y fuentes de datos en YAML o JSON, los usuarios pueden generar interfaces funcionales sin escribir código frontend personalizado. El sistema actúa como un constructor de paneles que transforma estas definiciones estructuradas en componentes visuales, admitiendo tanto la incrustación local como el despliegue remoto. El proyecto se distingue por permitir que los paneles se alojen y compartan a través de fragmentos controlados por versiones, permitiendo el acceso instantáneo a visualizaciones de datos sin requerir un backend dedicado. Admite actualizaciones dinámicas obteniendo archivos de configuración en tiempo de ejecución, y proporciona controles interactivos como menús desplegables que permiten a los usuarios filtrar y transformar vistas de datos directamente dentro del navegador. El framework se integra en aplicaciones web existentes como una dependencia modular, facilitando la inclusión de análisis directamente dentro de la jerarquía de vistas de un proyecto. Incluye herramientas automatizadas para generar declaraciones de tipo estático durante el proceso de compilación, asegurando la consistencia y proporcionando soporte para los desarrolladores a medida que definen sus estructuras de panel.