ReOrc docs
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  • About ReOrc
  • Set up and deployment
    • Set up organization
    • Install ReOrc agent
  • Getting started
    • 1. Set up a connection
      • BigQuery setup
    • 2. Create a project
    • 3. Create data models
    • 4. Build models in console
    • 5. Set up a pipeline
  • Connections
    • Destinations
      • Google Service Account
    • Integrations
      • Slack
  • Data modeling
    • Overview
    • Sources
    • Models
      • Model schema
      • Model configurations
    • Jinja templating
      • Variables
      • Macros
    • Materialization
    • Data lineage
    • Data tests
      • Built-in generic tests
      • Custom generic tests
      • Singular tests
  • Semantic modeling
    • Overview
    • Data Modelling vs Semantic Layer
    • Cube
      • Custom Dimension
      • Custom Measure
        • Aggregation Function
        • SQL functions and operators
        • Calculating Period-over-Period Changes
      • Relationship
    • View
      • Primary Dimension
      • Add Shared Fields
    • Shared Fields
    • Integration
      • Guandata Integration
      • Looker Studio
  • Pipeline
    • Overview
    • Modeling pipeline
    • Advanced pipeline
    • Job
  • Health tracking
    • Pipeline health
    • Data quality
  • Data governance
    • Data protection
  • Asset management
    • Console
    • Metadata
    • Version history
    • Packages and dependencies
  • DATA SERVICE
    • Overview
    • Create & edit Data Service
    • Data preview & download
    • Data sharing API
    • Access control
  • AI-powered
    • Rein AI Copilot
  • Settings
    • Organization settings
    • Project settings
    • Profile settings
    • Roles and permissions
  • Platform Specific
    • Doris/SelectDB
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On this page
  • What is Data Service?
  • Key benefits
  • Components
  1. DATA SERVICE

Overview

A introduction to the Data Service module of ReOrc.

What is Data Service?

The Data Service module simplifies data access for non-technical users by providing a user-friendly interface to interact with SQL-based data views. It allows business teams, external partners, or other stakeholders to explore, filter, and download data without needing to write or understand SQL queries.With Data Service, technical users (e.g., data engineers or analysts) can create and share pre-defined SQL queries, while non-technical users can easily access and interact with the resulting data through a visual interface. This eliminates the need for manual data extraction or complex query writing, making data more accessible and actionable for everyone.

Key benefits

  • Save as a Service: Users can save queries as services, enabling others to preview, download, or access the data through an API.

  • Ease of Use for Non-Tech Users: Non-technical users can easily preview data and perform further analysis without SQL knowledge.

  • Data Accessibility: External users can download data in Excel or extract it via API for seamless integration with their systems.

Components

  • Create & edit Data Service: Write, save, and manage SQL queries with a built-in editor and field configuration options.

  • Data preview & download: Preview, filter, sort, and export data to Excel/CSV for easy analysis and sharing.

  • Data sharing API: Share Data Services and access data via API keys.

  • Access control: Manage permissions and share Data Services with specific users or teams.

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Last updated 3 months ago