Introduction to Dataherald
Dataherald is an innovative tool designed to make querying relational data accessible through natural language. It acts as a bridge, transforming plain English questions into SQL queries, which can be incredibly powerful for enterprise-level data operations.
Key Features
- Natural Language Queries: Dataherald allows users to extract insights from databases by simply asking questions in English, eliminating the need for deep technical skills.
- Seamless Integration: Users can set up an API from their existing databases, enabling streamlined question-and-answer functionality within SaaS applications.
- ChatGPT Integration: The tool facilitates the creation of ChatGPT plugins using proprietary data, enhancing interactivity and data accessibility.
Core Components
Dataherald comprises four main components, each playing a critical role in its ecosystem:
- Engine: This is the heart of Dataherald, converting natural language into SQL. It powers the API for direct query purposes.
- Enterprise: This layer adds crucial features like authentication and user management, making Dataherald suitable for business environments.
- Admin-console: A graphical user interface for configuring and monitoring the Dataherald system, requiring the engine and enterprise components to function.
- Slackbot: A convenient Slack integration allowing users to query databases directly from a Slack channel, enhancing collaboration and accessibility.
Setting Up Locally
Running Dataherald locally involves a few straightforward steps:
-
Environment Setup: Each service requires specific environment variables. Reference the
.env.examplefiles provided in each service directory to configure your environment correctly. -
Service Execution: A single script is available to run all the services, creating a unified Docker network for efficient operation:
sh docker-run.sh
Contributing
Dataherald thrives as an open-source project in the ever-evolving data field. Contributions are welcome in any form, be it new features, infrastructure improvements, or enhanced documentation. Detailed contribution guidelines are available in the project's documentation.
Dataherald stands out as a powerful solution for enterprises looking to democratize access to data, enabling users at all levels to derive insights without needing specialized data knowledge.