ReOrc docs
Get ReOrc
English
English
  • 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
Powered by GitBook
On this page
  • Overview
  • What is Custom Measure?
  • Use Cases
  • Create a Custom Measure
  1. Semantic modeling
  2. Cube

Custom Measure

PreviousCustom DimensionNextAggregation Function

Last updated 15 days ago

Overview

A Custom Measure in ReOrc enables users to create new numerical calculations within a Cube, enhancing data analysis and reporting capabilities. These measures help define key business metrics that may not exist explicitly in the raw dataset.

What is Custom Measure?

A Custom Measure is a user-defined metric derived from existing fields using aggregation, mathematical operations, or conditional logic. These measures help refine insights and provide additional flexibility in data analysis.

Use Cases

  • New Business Metrics: Defining KPIs such as "Profit Margin" using ((Revenue - Cost) / Revenue).

  • Conditional Aggregations: Creating measures like "High-Value Orders" for transactions above a certain amount.

  • Ratio & Percentage Calculations: Computing values like "Conversion Rate" as ((Total Sales / Total Visitors) * 100).

  • Custom Weighting: Applying business rules to weigh certain values differently in calculations.

Create a Custom Measure

To create a custom dimension, follow these steps:

Ensure the cube's primary key has been set before proceed to create the custom dimension. Refer

  1. Click on + button, select Add a measure

  1. Fill in the details in the modal:

    1. Field label will be auto populate based on the Field name

    2. When entering the custom formula, you can click on the fields on the list to auto populate into the formula box.

    3. For Aggregations and sample use case, refer to Aggregation Function

  2. Click on Validate button to validate the formula

Ensure that the custom formula matches the type of database connected.

  1. Once no error detected, click on Add button to add the custom dimension into the cube.

Create Cube