70 Repos
Tools for constructing analytical dashboards and data visualization interfaces directly from backend data processing logic.
Distinguishing note: Focuses on the dashboarding aspect of data presentation, distinct from raw data storage or processing.
Explore 70 awesome GitHub repositories matching data & databases · Data Visualization Dashboards. Refine with filters or upvote what's useful.
Dieses Projekt ist ein von der Community gepflegtes Verzeichnis, das als umfassender Index für Software-Tools, Frameworks und Lehrmaterialien dient. Es fungiert als Open-Source-Wissensdatenbank, die verschiedene technische Bereiche und Ressourcen in einer strukturierten Taxonomie organisiert, um Entwickler bei der Suche nach qualitativ hochwertigen Inhalten zu unterstützen. Das Verzeichnis zeichnet sich durch ein dezentrales Peer-Review-Modell aus, bei dem unabhängige Mitwirkende Einträge kuratieren, verifizieren und aktualisieren, um Genauigkeit und Relevanz sicherzustellen. Alle Informationen werden in einem versionskontrollierten Flat-File-Markdown-Format gespeichert, was Plattformunabhängigkeit, Transparenz und Auditierbarkeit für die gesamte Sammlung gewährleistet. Das Projekt deckt ein breites Spektrum an Fähigkeiten ab, von der Entdeckung technischer Ressourcen über die berufliche Weiterentwicklung bis hin zum Wissensmanagement in der Softwareentwicklung. Es bietet Zugang zu strukturierten Lernpfaden, Infrastruktur- und Sicherheitstools, Datenmanagement-Dienstprogrammen sowie spezialisierten Ressourcen für Bereiche von der Gesundheitsversorgung bis zu den digitalen Geisteswissenschaften. Das Repository wird als öffentliche, versionskontrollierte Sammlung gepflegt, was einen programmatischen Zugriff und Community-gesteuerte Updates der strukturierten Daten ermöglicht.
Enables the construction of analytical dashboards and visualization interfaces from backend data.
Dieses Projekt ist ein von der Community kuratiertes Verzeichnis von Open-Source-Software, die für den Einsatz in privaten Serverumgebungen und Home-Labs konzipiert ist. Es dient als umfassende Ressource zur Entdeckung unabhängiger, selbst gehosteter Alternativen zu gängigen Cloud-Diensten und ermöglicht es Nutzern, die volle Datenhoheit und Kontrolle über ihre digitale Infrastruktur zu behalten. Das Verzeichnis ist durch eine hierarchische Taxonomie strukturiert, die eine riesige Sammlung von Anwendungen in logische Kategorien organisiert, von Medienmanagement und Datenanalyse bis hin zu privater Kommunikation und Tools für die Teamproduktivität. Es zeichnet sich durch einen kollaborativen Peer-Review-Prozess aus, bei dem Community-Mitglieder die Qualität und Relevanz jeder Einreichung validieren, um sicherzustellen, dass das Verzeichnis korrekt und zuverlässig bleibt. Das Projekt deckt ein breites Spektrum an Fähigkeiten ab, einschließlich Infrastruktur-Automatisierung, containerbasierter Service-Bereitstellung und deklarativem Konfigurationsmanagement. Diese Tools unterstützen Nutzer bei der Aufrechterhaltung reproduzierbarer Serverumgebungen und der Verwaltung komplexer Service-Abhängigkeiten auf privater Hardware. Das Verzeichnis wird als versionskontrolliertes Repository gepflegt, wodurch sichergestellt wird, dass alle Updates und Community-gesteuerten Änderungen nachverfolgt und transparent sind.
Processes and visualizes structured data, server logs, and business metrics through self-hosted dashboards.
Gradio is a Python library that enables the creation of interactive web applications by converting functions into browser-based interfaces. It functions as a declarative framework where developers define input and output components to automatically generate web forms, visualizations, and data-driven dashboards. By abstracting away manual web markup, the library allows for the rapid construction of interfaces for machine learning models, research demonstrations, and analytical workflows within a single environment. The platform distinguishes itself by automatically exposing internal applicatio
Creating internal data visualization tools and analytical dashboards quickly by connecting Python data processing scripts directly to modular web components.
This project is a distributed, document-oriented database system designed to store information in flexible, hierarchical structures. It supports horizontal scaling through automated sharding and maintains high availability across global clusters using a multi-node replication protocol. By executing multi-document operations as atomic units, the system ensures data integrity and consistency across distributed environments. The platform distinguishes itself by integrating advanced vector-based indexing, which enables semantic similarity searches alongside traditional geospatial and lexical quer
Connects standard reporting tools to document collections to create visual dashboards and perform deep analysis on stored information.
Dash is a Python-based framework for building analytical web applications and reactive data dashboards. It allows developers to connect data science and machine learning code to interactive web interfaces without writing JavaScript, serving as a backend-driven tool for defining layouts and managing state. The framework integrates the Plotly charting engine to render a wide variety of complex charts and financial graphs. It distinguishes itself through a reactive callback system that links user input components to data visualizations, enabling the creation of business intelligence dashboards a
Provides a framework for constructing analytical dashboards and data visualization interfaces directly from Python backend logic.
This project is an open-source, privacy-focused web analytics platform designed for high-throughput data ingestion and multi-tenant data management. It provides a cookie-less tracking engine that captures visitor interactions using ephemeral request metadata, ensuring comprehensive traffic visibility while maintaining strict privacy standards. The architecture utilizes an event-driven ingestion pipeline and aggregated metric storage to decouple data collection from processing, enabling efficient long-term retrieval and responsive dashboard performance. What distinguishes this platform is its
Supports exporting and visualizing analytics data in third-party business intelligence tools.
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
Provides a drag-and-drop interface for constructing interactive analytical dashboards from diverse data sources.
ThingsBoard is an IoT device management platform designed for provisioning, monitoring, and managing large fleets of hardware devices and assets across multiple customers. It functions as a microservices infrastructure that allows the deployment of data collection and management services as independent containerized units for scaling. The platform includes a rule-based stream processor that transforms incoming device data and triggers alarms using customizable rule chains. It also provides a data visualization suite consisting of dashboards and widgets to display real-time telemetry and syste
Collects device telemetry and displays it through custom widgets and shared analytical dashboards.
This platform is a modular, metadata-driven framework designed for building custom business applications and data management systems without traditional coding. It functions as a low-code environment where data models, user interfaces, and business logic are defined through visual configurations rather than hardcoded views. The architecture supports multi-tenant isolation, allowing multiple independent applications to run within a single shared memory space while maintaining strict logical separation of data and configurations. What distinguishes this system is its deep integration of artific
Builds interactive dashboards and charts by mapping data queries to visual components using visual builders.
Gentelella is a collection of pre-configured interface templates and a component library designed for building administration panels, data dashboards, and internal management consoles. It provides a Bootstrap 5 based framework that includes accessible web interface templates and PWA-ready dashboard shells. The project features specialized templates for data visualization, utilizing modular chart factories to render line, bar, radar, and heatmap visualizations. It includes a set of ready-to-use interface elements for enterprise prototyping, such as kanban boards, file managers, and interactive
Includes templates for analytical dashboards featuring line, bar, radar, and heatmap visualizations.
Kibana is a browser-based data exploration and visualization platform designed for interacting with information stored in distributed search engines. It serves as a centralized interface for analyzing structured and unstructured data, enabling users to build custom dashboards, generate interactive charts, and map complex datasets to uncover trends and actionable insights. Beyond visualization, the platform functions as a comprehensive management console for infrastructure operations. It provides tools for configuring security policies, managing data indices, and monitoring system health. The
Provides a web interface for visualizing and analyzing data stored in distributed search engines.
Excelize is a library for reading and writing spreadsheet files in the Office Open XML format. It provides a comprehensive suite of tools for programmatically creating, modifying, and analyzing workbooks, worksheets, and cell data, ensuring compatibility across various office software suites through structured XML serialization. The library distinguishes itself with a built-in formula calculation engine that evaluates complex mathematical and logical expressions directly against workbook data. It also features a memory-mapped streaming architecture, which allows for the efficient processing o
Creates interactive charts and tables from stored data for real-time insights.
Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance graphics and data dashboards that render in web browsers. It serves as a tool for generating standalone HTML documents, embedded components for digital notebooks, and full-stack web applications powered by a Python backend. The project distinguishes itself through its ability to handle large or streaming datasets while maintaining smooth interactivity. It enables linked brushing across multiple views, allowing data selected in one plot to automatically highlight corresponding data i
Enables the composition of interactive plots and controls into comprehensive visual applications for complex data analysis.
Vue Manage System is a type-safe administrative dashboard framework built with Vue 3 and Element Plus. It serves as a management template for backend systems, integrating role-based access control to restrict pages and actions based on assigned user permissions. The project distinguishes itself through a comprehensive set of administrative tools, including a data visualization dashboard with interactive charts and a content management system featuring rich text editing and image cropping utilities. It utilizes TypeScript for static typing and Pinia for centralized state management. The syste
Provides an interactive dashboard for visualizing system metrics and data trends through charts and tables.
OpenObserve is a unified observability data platform designed to ingest, store, and analyze logs, metrics, and traces. It functions as a cloud-native monitoring tool that centralizes telemetry from diverse sources, including standard collectors and cloud service providers, into a single, scalable system. By utilizing a columnar storage engine backed by object storage, the platform enables efficient long-term data retention and high-performance analytical querying. The platform distinguishes itself through deep integration with artificial intelligence, allowing users to query data using natura
Constructs visual dashboards and monitoring panels based on natural language descriptions of desired metrics, error rates, or latency views.
Twint is an open-source intelligence and data extraction framework designed to gather public social media information. It functions as a command-line utility that retrieves posts, user profiles, and follower lists directly from web interfaces, bypassing the need for official platform developer credentials or authentication keys. The tool distinguishes itself by enabling automated, large-scale data collection through terminal-based orchestration. It supports granular filtering by keywords, geographic locations, time ranges, and account status, allowing researchers to build targeted datasets fo
Integrates with visualization tools to present gathered data in interactive dashboards.
Soybean Admin is a type-safe frontend management boilerplate and dashboard template built with Vue 3, Vite, and TypeScript. It provides a pre-configured foundation for creating enterprise administrative interfaces, utilizing the NaiveUI component framework and UnoCSS for utility-first styling. The project distinguishes itself through automated workflow tools, including file-system-based route generation and a command-line interface for automating git commits and project deployments. It implements a comprehensive security model featuring both static and dynamic role-based access control to res
Combines interactive data tables and complex charts into analytical dashboards for rendering backend metrics.
This project is a curated directory of software, frameworks, and educational resources designed for building, scaling, and maintaining distributed data processing and storage architectures. It serves as a comprehensive index for the distributed computing ecosystem, helping users identify the appropriate tools for managing large-scale information systems. The repository functions as a central hub for data engineering, offering categorized access to technologies that support batch and stream processing, machine learning, and interactive querying. By organizing these resources, it assists in the
Enables the creation of interactive dashboards and charts to visualize complex data insights.
OpenSearch is a distributed search and analytics engine designed for indexing, searching, and analyzing massive volumes of structured and unstructured data in real time. It functions as a comprehensive platform that integrates enterprise-grade search capabilities, a vector database for high-dimensional similarity lookups, and a unified observability suite for monitoring logs, metrics, and traces across complex distributed environments. The platform distinguishes itself through its support for agentic workflow automation, allowing users to orchestrate multi-agent tasks and integrate foundation
Transforms raw data into interactive charts, graphs, and dashboards to facilitate real-time analysis and reporting.
This project is a collection of specialized study guides and roadmaps centered on computer science, data engineering, and machine learning fundamentals. It provides a structured curriculum of technical competencies, tools, and skills required to transition into professional data engineering roles. The project features a data engineering skill map that visually organizes databases, processing architectures, and infrastructure tools. It also includes a machine learning learning path covering supervised and unsupervised learning techniques alongside model operations. The curriculum covers broad
Utilizes dashboards and notebooks to render datasets and visualize trends for analytical insights.