Data schema
A data schema describes the structure and rules of data. It defines fields and data types, for example; provenance and freshness are additional questions.
A data schema describes how data should be structured. It can define fields, data types, relationships and constraints. The schema might concern a record or an exchanged message, for example.
Agree to keep an identifier as text
In a fictional product data exchange, the item identifier "0042" should remain a string. A suitable schema can define the field’s type. That alone does not establish which system may assign this identifier or which state of the product data is transferred.
Check structure and meaning together
Confluent describes a schema as a specification for the structure of message data. JSON Schema is one possible language for these rules with JSON data. The meaning of a value also needs agreement: a stock field might mean available stock or total stock, for example. The same field name and numeric type do not answer that question. Alongside the structure, check the meaning, provenance and required time context of the data.
Sources
Related terms
- JSON SchemaJSON Schema describes the structure and constraints of JSON data. A validator checks these rules; conformance alone does not establish business correctness.
- Transactional inboxA transactional inbox uses durable message records to protect local processing against duplicate deliveries.
- Message acknowledgementA message acknowledgement tells the broker that a delivery has been received or processed according to the agreed rule.
- Retry jitterRetry jitter varies waiting times randomly to spread retries and reduce simultaneous requests from many clients.
- Test tenantA logically bounded customer context of a multitenant application, configured for testing.
- Webhook replayWebhook replay means sending a webhook notification again. Deliberate recovery and replay attacks require different checks.
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