Schema
Define field names, data types, permitted values, required/optional flags, and cardinality. Include example records and machine-readable schema (JSON Schema, XSD, or Avro) to support automated validation and parsing.
Adopting a Data Management Format improves interoperability, reduces data errors, and accelerates onboarding of datasets. It provides auditable structure for governance, supports regulatory requirements such as HIPAA or IRS recordkeeping, and clarifies responsibilities for data stewardship across teams.
Data architects, data stewards, compliance officers, and engineers commonly prepare the Data Management Format to standardize datasets and metadata across systems.
The format helps cross-functional teams collaborate by documenting responsibilities, handoffs, and escalation paths for data issues.
Define field names, data types, permitted values, required/optional flags, and cardinality. Include example records and machine-readable schema (JSON Schema, XSD, or Avro) to support automated validation and parsing.
Specify descriptive, administrative, and provenance metadata fields such as title, owner, creation date, source system, and lineage to aid discovery and governance workflows, including standard vocabularies and tags.
Document validation rules, error codes, acceptable thresholds, and sample test cases. Define automated checks and reporting for schema conformance, null rates, range checks, and referential integrity to reduce ingestion failures.
Include version identifiers, change logs, publication dates, and migration notes. Require backward/forward compatibility rules and deprecation schedules to manage producer and consumer updates without data loss.
Define roles, permissions, authentication methods, and data masking rules. Specify authorized consumers, encryption requirements in transit and at rest, and logging requirements for access audits.
Set delivery channels, file formats, compression, batching frequency, and acknowledgement protocols. Describe retries, backoff policies, and SLA expectations for timely and reliable data transfer, including error reporting.
| Field Configuration and Purpose Guide | Setting name | Configuration details for workflow |
|---|---|
| Field Recognition | Enable Magic fields | Auto-detect names, dates, and IDs |
| Conditional Logic | Define conditional fields | Rules based on values or roles |
| Signer Roles | Assign signer roles | Editor, Approver, Reviewer, Viewer |
| Notifications | Notifications and webhooks | Email, Slack, or API callbacks |
Ensure your signing and distribution platform supports required formats, integrations, and security controls before using the Data Management Format.
Provide at least two weeks for review and approval.
Run automated checks within 48–72 hours of submission.
Coordinate monthly or milestone-based schema deployments.
Expect 1–5 business days for manual review.
Retention begins on effective date or publication date.
Optica Ventures standardized data schemas to reduce onboarding friction and improve data quality across portfolio companies.
Martin Properties used a Data Management Format to standardize lease and tenant data for faster closings and accurate reporting.
| signNow | DocuSign | Adobe Sign | PandaDoc | HelloSign | |
|---|---|---|---|---|---|
| Starting Price | $8/user/mo | $15/user/mo | $14/user/mo | $19/user/mo | $15/user/mo |
| Free Trial | 7-day free trial | Varies by vendor | Varies by vendor | Varies by vendor | Varies by vendor |
| Bulk Send | Yes (Premium) | Yes | Yes | Yes | No |
| Audit Trail | Yes | Yes | Yes | Yes | Yes |
| HIPAA Compliant | Yes (BAA required) | Yes | Yes | No | No |
| Envelope Cap | No envelope cap | 100 envelopes/user/year | Varies by plan | Varies by plan | Varies by plan |