Templates

Robotics Events

Data Contract Template

Ensure data from robotics operational events is fresh, complete, and reliable before it is used for operational monitoring, event-driven analytics, incident review, and process performance measurement.

Data contract description

This data contract is designed for a robotics startup that relies on machine-generated operational events to measure how its automation systems are performing across facilities, machines, work units, and processes. In this use case, the contract supports a production event stream used for operational analytics and business-critical metrics, where unreliable event delivery or inconsistent structure would slow analysis, weaken visibility into system behavior, and make it harder to support high-stakes customer reporting.

Dataset

Defines the dataset this contract applies to, including its source and scope. This is the single point of reference for what data is being validated and protected.

Dataset checks

Validations that apply to the dataset as a whole, including schema stability, data freshness, and overall structural guarantees. This contract includes a schema check that prevents unexpected columns and unexpected column reordering, a row count check to ensure the dataset is not empty, and a freshness check that requires data to be less than two hours old based on ingest_time.

Column checks

Column-level rules to ensure completeness, correctness, and consistency for individual fields. This contract enforces that event_id, event_type, event_time, ingest_time, facility_id, machine_id, work_unit_id, and process_id are not missing, and it requires event_id to be unique. It restricts event_type to approved values (state_change, cycle_complete, alarm_raised, measurement_recorded) and applies length guardrails to the main identifier fields so malformed or unusable values are caught early.

robotics_events_data_contract.yaml

dataset

checks:
  - schema:
      allow_extra_columns: false
      allow_other_column_order: false
  - row_count:
      threshold:
        must_be_greater_than: 0
  - freshness:
      column: ingest_time
      threshold:
        unit: hour
        must_be_less_than: 2

columns:
  - name: event_id
    data_type: string
    checks:
      - missing:
      - duplicate:
      - invalid:
          name: "Event ID length guardrail"
          valid_min_length: 1
          valid_max_length: 128
  - name: event_type
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Valid event types"
          valid_values:
            - state_change
            - cycle_complete
            - alarm_raised
            - measurement_recorded
  - name: event_time
    data_type: timestamp
    checks:
      - missing:
  - name: ingest_time
    data_type: timestamp
    checks:
      - missing:
  - name: facility_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Facility ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64
  - name: machine_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Machine ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64
  - name: work_unit_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Work Unit ID flexibility"
          valid_min_length: 1
          valid_max_length: 64
  - name: process_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Process ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64

Data contract description

Dataset

Defines the dataset this contract applies to, including its source and scope. This is the single point of reference for what data is being validated and protected.

Dataset checks

Column checks

robotics_events_data_contract.yaml

dataset

checks:
  - schema:
      allow_extra_columns: false
      allow_other_column_order: false
  - row_count:
      threshold:
        must_be_greater_than: 0
  - freshness:
      column: ingest_time
      threshold:
        unit: hour
        must_be_less_than: 2

columns:
  - name: event_id
    data_type: string
    checks:
      - missing:
      - duplicate:
      - invalid:
          name: "Event ID length guardrail"
          valid_min_length: 1
          valid_max_length: 128
  - name: event_type
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Valid event types"
          valid_values:
            - state_change
            - cycle_complete
            - alarm_raised
            - measurement_recorded
  - name: event_time
    data_type: timestamp
    checks:
      - missing:
  - name: ingest_time
    data_type: timestamp
    checks:
      - missing:
  - name: facility_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Facility ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64
  - name: machine_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Machine ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64
  - name: work_unit_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Work Unit ID flexibility"
          valid_min_length: 1
          valid_max_length: 64
  - name: process_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Process ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64

Data contract description

robotics_events_data_contract.yaml

dataset

checks:
  - schema:
      allow_extra_columns: false
      allow_other_column_order: false
  - row_count:
      threshold:
        must_be_greater_than: 0
  - freshness:
      column: ingest_time
      threshold:
        unit: hour
        must_be_less_than: 2

columns:
  - name: event_id
    data_type: string
    checks:
      - missing:
      - duplicate:
      - invalid:
          name: "Event ID length guardrail"
          valid_min_length: 1
          valid_max_length: 128
  - name: event_type
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Valid event types"
          valid_values:
            - state_change
            - cycle_complete
            - alarm_raised
            - measurement_recorded
  - name: event_time
    data_type: timestamp
    checks:
      - missing:
  - name: ingest_time
    data_type: timestamp
    checks:
      - missing:
  - name: facility_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Facility ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64
  - name: machine_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Machine ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64
  - name: work_unit_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Work Unit ID flexibility"
          valid_min_length: 1
          valid_max_length: 64
  - name: process_id
    data_type: string
    checks:
      - missing:
      - invalid:
          name: "Process ID length guardrail"
          valid_min_length: 1
          valid_max_length: 64

How to Enforce Data Contracts with Soda

Embed data quality through data contracts at any point in your pipeline.

# pip install soda-{data source} for other data sources

pip install soda-postgres

# verify the contract locally against a data source

soda contract verify -c contract.yml -ds ds_config.yml

# publish and schedule the contract with Soda Cloud

soda contract publish -c contract.yml -sc sc_config.yml

Check out the CLI documentation to learn more.

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