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Metad

Open-Source AI Platform for Enterprise Data Analysis, Indicator Management and System Orchestration

Visitors ocap on npm   License: AGPL v3 Gitpod Ready-to-Code

Metad Analytics Platform

💡 What's New

Xpert AI

Xpert AI is an enterprise-level AI system that integrates BI (Business Intelligence) indicators management and intelligent dialogue functionality. It features modules such as a knowledge base, data analysis toolset (ChatBI, ChatDB, Search), and more. It acts as a digital expert, providing intelligent assistant copilot services and is deeply integrated with Feishu (Lark) bots. Xpert AI leverages advanced AI technology to offer efficient decision support and information management for enterprises, helping users quickly obtain data insights, optimize business processes, and enhance overall operational efficiency.

More details

ChatBI: Natural Language-Driven Business Intelligence Analysis

ChatBI is an innovative feature we are introducing, combining chat functionality with business intelligence (BI) analysis capabilities. It offers users a more intuitive and convenient data analysis experience through natural language interaction.

chatbi5.mp4

🎯 Mission

"One Table, One Model, One Indicator System"

Simple, efficient, integrated. Users can conduct analysis by simply dealing with one fact table. Through the multi-dimensional modeling function provided by the platform, a comprehensive set of indicators can be quickly obtained within the unified semantic model.

🌟 What is it

Metad Platform - Open-Source Analytics Platform for Enterprise Data Analysis Indicator Management and Reporting.

  • Semantic Model: Perform multi-dimensional data modeling and analysis, allowing users to explore data from various dimensions and hierarchies.
  • Story Dashboard: Create compelling visual narratives with Story Dashboards, combining interactive visualizations, narrative elements, and data-driven storytelling.
  • Indicator Management: Easily define, manage, and monitor key performance indicators (KPIs) to ensure data quality, consistency, and effective performance analysis.
  • AI Copilot: Benefit from AI-driven insights and recommendations to enhance decision-making processes and identify actionable opportunities.

Story Workspace

Indicator Application

✨ Features

Main features:

  • Data Sources: connects with lots of different databases and data warehouses.
    • OLAP: SAP BW/BPC, HANA, SSAS, Mondrian, Kylin etc.
    • MPP DB: StarRocks, Apache Doris, ClickHouse etc.
    • SQL DB: MySQL, PostgreSQL etc.
    • MR Source: Hive, Trino etc.
  • Semantic Model: Supports the unified semantic modeling of two olap engines: MDX and SQL, and supports multi-dimensional modeling and analysis.
    • Query Lab: An environment for executing and analyzing SQL or MDX queries, with AI Copilot to assist in writing and optimizing SQL or MDX queries.
    • Virtual Cube: combine dimensions and measures from multiple cubes.
    • Access Control: The access control of the cube defined based on single role or combined role to the row level.
    • External Cube: support cube from third-party multiple-dimensional data source, such as SSAS, SAP BW/BPC etc.
    • Calculated Members: support calculated dimension members and calculated measures using MDX or SQL expression.
  • Project: A project is a collection of story dashboards, indicators and other resources that are used to create and deliver analytics content collaborating with colleagues.
  • Indicator Management: Define, manage, and monitor key performance indicators (KPIs) to ensure data quality, consistency, and effective performance analysis.
    • Indicator registration
    • Indicator certification
    • Indicator business area
    • Derivative indicator
    • Indicator measure
  • Indicator Market: Publish and share indicators with other users in one place.
  • Indicator Application: View and analyze indicators in a dedicated single page application.
  • Story Dashboard: Create compelling visual narratives with Story Dashboards, combining interactive visualizations, narrative elements, and data-driven storytelling.
    • Bigview Dashboard: A story dashboard suitable for large screen display, supporting data automatic refresh and scrolling display.
    • Mobile Design: support mobile terminal adaptive design, support mobile terminal browser access.
    • Story Template: Create and share a unified style and layout template of story.
    • Execution Explain: Explain the execution process of SQL or MDX queries inculde query statement, slicers, query result and chart options.
  • AI Copilot: assist users quickly design and implement story dashboards and indicators.
    • /query command to execute SQL or MDX queries.
    • /story command to create a story dashboard.
    • /indicator command to create an indicator.
    • /clear command to clear the screen.
    • ...

Basic feartures of the platform:

  • Multi-tenant
  • Multiple Organizations Management
  • Home Dashboard
  • Roles / Permissions
  • Tags / Labels
  • Custom SMTP
  • Email Templates
  • Copilot
  • Country
  • Currency
  • Logger
  • Storage File
  • User
  • Invite
  • Business Area
  • Certification
  • Dark / Light and other themes

🌼 Screenshots

Show / Hide Screenshots

Pareto analysis open in new tab

Pareto analysis Screenshot

Product profit analysis open in new tab

Product profit analysis Screenshot

Reseller analysis open in new tab

Reseller analysis Screenshot

Bigview dashboard open in new tab

Bigview dashboard Screenshot

Indicator application open in new tab

Indicator application Screenshot

Indicator mobile app open in new tab

Indicator mobile app Screenshot

🔗 Links

💻 Demo, Downloads, Testing and Production

Demo

Metad Analytics Platform Demo at https://app.mtda.cloud.

Notes:

  • You can generate samples data in the home dashbaord page.

Downloads

You can download Metad Desktop Agent use to connect to your local data sources.

Production (SaaS)

Metad Analytics Platform SaaS is available at https://app.mtda.cloud.

Note: it's currently in Alpha version / in testing mode, please use it with caution!

🧱 Technology Stack and Requirements

For Production, we recommend:

Note: thanks to TypeORM, OCAP will support lots of DBs: SQLite (default, for demos), PostgreSQL (development/production), MySql, MariaDb, CockroachDb, MS SQL, Oracle, MongoDb, and others, with minimal changes.

See also README.md and CREDITS.md files in relevant folders for lists of libraries and software included in the Platform, information about licenses, and other details

📄 Documentation

Please refer to our official Platform Documentation and to our Wiki (WIP) or api references for more details.

🚀 Quick Start

Please check our Wiki - Development to get started quickly.

💌 Contact Us

🛡️ License

We support the open-source community.

This software is available under the following licenses:

Please see LICENSE for more information on licenses.

🍺 Contribute

  • Please give us ⭐ on Github, it helps!
  • You are more than welcome to submit feature requests in the ocap repo
  • Pull requests are always welcome! Please base pull requests against the develop branch and follow the contributing guide.