ReOrc docs
Get ReOrc
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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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Getting started

This guide shows you how to get started with ReOrc

PreviousInstall ReOrc agentNext1. Set up a connection

Last updated 15 days ago

This guide covers the capabilities currently available in the beta release, allowing you to connect to a database, create data models using sources and SQL models, build pipelines incorporating these models, and schedule job runs directly from the pipeline.

Prerequisites:

  • You have a Recurve account. If not, you can sign up here:

  • You have been invited to an organization, with environments and workers running. For instructions, see: Set up and deployment.

Step-by-step workflow

Follow these steps to get started with Recurve:

    • Connect ReOrc to your data sources (relational database, data warehouse).

    • Authenticate and configure the connection details.

    • Set up a project as a collaborative space for your team.

    • Configure an analytics database to store and process the transformed data of the project.

    • Reference your raw data as sources.

    • Define your transformation logic using models.

    • Add tests to validate that your models are working properly.

    • Execute model builds in console and run associated data tests to verify transformations.

    • Debug failed tests, optimize performance, and iterate models based on validation results.

    • Automate the workflow in a pipeline by chaining together your data models.

    • Configure the pipeline execution and schedule in a job.

    • Monitor the pipeline through the Health Tracking dashboard.

Throughout these guides, we'll introduce you to the key components of Recurve and provide necessary links for more detailed information on each step. Let's get started!

ReOrc
Set up a connection
Create a project
Create data models
Build the models in console
Set up a pipeline