Data Scope

Data Scope is an open-source data quality platform designed to help organizations monitor, validate, and improve their data quality across various data sources.

Overview

Data Scope provides a comprehensive solution for data quality management with features including:

• Data quality monitoring and validation
• Customizable data quality rules
• Support for multiple data sources
• Anomaly detection and alerting
• User-friendly dashboard for data quality visualization
• Natural language query interface
• Low-code rule configuration

Architecture

Data Scope follows a modular architecture with the following key components:

• Web UI: User interface for configuring rules, viewing results, and managing data quality
• API Layer: RESTful APIs for interacting with the platform
• Core Engine: Handles rule execution, validation, and data processing
• Data Source Connectors: Interfaces with various data sources
• Storage Layer: Manages metadata and validation results

For more details, see Architecture Documentation.

Getting Started

Prerequisites

• Java 8 or higher
• MySQL 5.7 or higher
• Redis (for caching)
• Maven 3.6 or higher

Installation

1. Clone the repository:

   git clone https://github.com/im47cn/data-scope.git
   cd Data Scope

2. Configure the database:

   • Create a database named datainsight
   • Update database configuration in src/main/resources/application.yml

3. Build the project:

   mvn clean package

4. Run the application:

   java -jar target/datainsight.jar

5. Access the web interface at http://localhost:8080

Features

Data Quality Rules

Data Scope supports various types of data quality rules:

• Completeness checks
• Uniqueness validation
• Referential integrity
• Pattern matching
• Statistical validations
• Custom SQL-based rules

Data Source Support

• MySQL
• PostgreSQL
• Oracle
• SQL Server
• Hive
• Spark
• More connectors coming soon

Alerting and Notifications

Configure alerts based on rule violations with notification channels:

• Email
• Slack
• Webhook
• Custom integrations

Project Roadmap

Based on our sprint planning documents:

• Sprint 1: Core platform setup, basic UI, and initial data source connectors
• Sprint 2: Enhanced rule engine, additional data sources, and improved dashboard
• Sprint 3: Advanced analytics, natural language query interface, and API enhancements

See Project Plan for more details.

Contributing

We welcome contributions to Data Scope! Please see our Contributing Guidelines for more information.

License

This project is licensed under the Apache License 2.0.

Documentation

For more detailed documentation, please refer to:

• Architecture Design
• Project Specification
• Architecture Decision Records
• API Documentation (when running locally)

Contact

For questions or support, please open an issue on GitHub or contact the project maintainers.