ahuachen/ocap

🛰 Metad® Open Platform for Enterprise Data Analysis, Indicator Management and Reporting

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

Metad Analytics Platform

💡 What's New

We released new version which includes AI Copilot in query lab, it can assit you to write and optimize SQL or MDX queries.

🌟 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.

✨ Features

Main features:

• Data Sources: connects with lots of different databases and data warehouses.
• 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.

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 / Thin and other themes

🌼 Screenshots

Show / Hide Screenshots

Sales overview open in new tab

Pareto analysis open in new tab

Product profit analysis open in new tab

Reseller analysis open in new tab

Bigview dashboard open in new tab

Indicator application open in new tab

Indicator mobile app open in new tab

🔗 Links

• https://mtda.cloud/en/ check more information about the platform at the official website.
• https://mtda.cloud/en/docs/ (WIP) check the official documentation and tutorials for more details.
• https://mtda.cloud/en/blog/ Check out the official blog for the latest updates.
• https://app.mtda.cloud/ Login to Metad analytics platform for free use.

💻 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

• TypeScript language
• NodeJs / NestJs
• Nx
• Angular
• RxJS
• TypeORM
• ECharts
• Java
• Mondrian

For Production, we recommend:

• PostgreSQL
• PM2

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).

🚀 Quick Start

With Docker Compose

• Clone repo.
• Make sure you have Docker Compose installed locally.
• Copy .env.compose file into .env file in the root of mono-repo (the file contains default env variables definitions).
• Run docker-compose -f docker-compose.demo.yml up, if you want to run the platform using our prebuild Docker images. (Note: it uses latest images pre-build automatically from head of main branch using GitHub CI/CD.)
• Run docker-compose up, if you want to build everything (code and Docker images) locally. (Note: this is extremely long process, option above is much faster.)
• Open http://localhost:4200 in your browser.
• The first time you will enter the onborading page. Follow the prompts to complete the initial settings ( organization, samples and connect your data source), and then you can start using it.
• Enjoy!

Manually

Required

• Install NodeJs LTS version or later, e.g. 18.x.
• Install Yarn (if you don't have it) with npm i -g yarn.
• Install NPM packages and bootstrap solution using the command yarn bootstrap.
• Copy .env.local file into .env and adjust settings in the file which is used in local runs.
• Run command docker-compose -f docker-compose.dev.yml up -d to start PostgreSQL database and redis services.
• Run both API, UI and OLAP engine with a single command: yarn start, or run them separately with yarn start:api, yarn start:cloud and yarn start:olap.
• Open Metad UI on http://localhost:4200 in your browser (API runs on http://localhost:3000/api).
• Onboarding...
• Enjoy!

Production

• For simple deployment scenarios (e.g. for yourself or your own small organization), check our Docker Compose file, which we are using to deploy Metad Analytics Platform to docker cluster.
• For production deployment scenarios (e.g. for enterprise organization), check our Kubernetes configurations, which we are using to deploy Metad Analytics Platform into Kubernetes platform, for example Aliyun k8s cluster.

💌 Contact Us

• For business inquiries: mailto:service@mtda.cloud
• Metad Platform @ Twitter

🛡️ License

We support the open-source community.

This software is available under the following licenses:

• Metad Analytics Platform Community Edition
• Metad Analytics Platform Small Business
• Metad Analytics Platform Enterprise

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.