Data Contract Specification

Data contracts bring data providers and data consumers together.

A data contract is a document that defines the structure, format, semantics, quality, and terms of use for exchanging data between a data provider and their consumers. A data contract is implemented by a data product's output port or other data technologies. Data contracts can also be used for the input port to specify the expectations of data dependencies and verify given guarantees.

The data contract specification defines a YAML format to describe attributes of provided data sets. It is data platform neutral and can be used with any data platform, such as AWS S3, Google BigQuery, Azure, Databricks, and Snowflake. The data contract specification is an open initiative to define a common data contract format. It follows OpenAPI and AsyncAPI conventions.

Data contracts come into play when data is exchanged between different teams or organizational units, such as in a data mesh architecture. First, and foremost, data contracts are a communication tool to express a common understanding of how data should be structured and interpreted. They make semantic and quality expectations explicit. They are often created collaboratively in workshops together with data providers and data consumers. Later in development and production, they also serve as the basis for code generation, testing, schema validations, quality checks, monitoring, access control, and computational governance policies.

The specification comes along with the Data Contract CLI, an open-source tool to develop, validate, and enforce data contracts.

IntelliJ, VS Code and other common IDEs allow you to use autocompletions without additional configuration.

Note: The term "data contract" refers to a specification that is usually owned by the data provider and thus does not align with a "contract" in a legal sense as a mutual agreement between two parties. The term "contract" may be somewhat misleading, but it is how it is used in practice. The mutual agreement between one data provider and one data consumer is the "data usage agreement" that refers to a data contract. Data usage agreements have a defined lifecycle, start/end date, and help the data provider to track who accesses their data and for which purposes.

Version

0.9.3 (Changelog)

Example

dataContractSpecification: 0.9.3
id: urn:datacontract:checkout:orders-latest
info:
  title: Orders Latest
  version: 1.0.0
  description: |
    Successful customer orders in the webshop. 
    All orders since 2020-01-01. 
    Orders with their line items are in their current state (no history included).
  owner: Checkout Team
  contact:
    name: John Doe (Data Product Owner)
    url: https://teams.microsoft.com/l/channel/example/checkout
servers:
  production:
    type: s3
    location: s3://datacontract-example-orders-latest/data/{model}/*.json
    format: json
    delimiter: new_line
terms:
  usage: |
    Data can be used for reports, analytics and machine learning use cases.
    Order may be linked and joined by other tables
  limitations: |
    Not suitable for real-time use cases.
    Data may not be used to identify individual customers.
    Max data processing per day: 10 TiB
  billing: 5000 USD per month
  noticePeriod: P3M
models:
  orders:
    description: One record per order. Includes cancelled and deleted orders.
    type: table
    fields:
      order_id:
        $ref: '#/definitions/order_id'
        required: true
        unique: true
        primary: true
      order_timestamp:
        description: The business timestamp in UTC when the order was successfully registered in the source system and the payment was successful.
        type: timestamp
        required: true
        example: "2024-09-09T08:30:00Z"
      order_total:
        description: Total amount the smallest monetary unit (e.g., cents).
        type: long
        required: true
        example: "9999"
      customer_id:
        description: Unique identifier for the customer.
        type: text
        minLength: 10
        maxLength: 20
      customer_email_address:
        description: The email address, as entered by the customer. The email address was not verified.
        type: text
        format: email
        required: true
        pii: true
        classification: sensitive
      processed_timestamp:
        description: The timestamp when the record was processed by the data platform.
        type: timestamp
        required: true
  line_items:
    description: A single article that is part of an order.
    type: table
    fields:
      lines_item_id:
        type: text
        description: Primary key of the lines_item_id table
        required: true
        unique: true
        primary: true
      order_id:
        $ref: '#/definitions/order_id'
        references: orders.order_id
      sku:
        description: The purchased article number
        $ref: '#/definitions/sku'
definitions:
  order_id:
    domain: checkout
    name: order_id
    title: Order ID
    type: text
    format: uuid
    description: An internal ID that identifies an order in the online shop.
    example: 243c25e5-a081-43a9-aeab-6d5d5b6cb5e2
    pii: true
    classification: restricted
  sku:
    domain: inventory
    name: sku
    title: Stock Keeping Unit
    type: text
    pattern: ^[A-Za-z0-9]{8,14}$
    example: "96385074"
    description: |
      A Stock Keeping Unit (SKU) is an internal unique identifier for an article. 
      It is typically associated with an article's barcode, such as the EAN/GTIN.
examples:
  - type: csv # csv, json, yaml, custom
    model: orders
    description: An example list of order records.
    data: | # expressed as string or inline yaml or via "$ref: data.csv"
      order_id,order_timestamp,order_total,customer_id,customer_email_address,processed_timestamp
      "1001","2030-09-09T08:30:00Z",2500,"1000000001","[email protected]","2030-09-09T08:31:00Z"
      "1002","2030-09-08T15:45:00Z",1800,"1000000002","[email protected]","2030-09-09T08:31:00Z"
      "1003","2030-09-07T12:15:00Z",3200,"1000000003","[email protected]","2030-09-09T08:31:00Z"
      "1004","2030-09-06T19:20:00Z",1500,"1000000004","[email protected]","2030-09-09T08:31:00Z"
      "1005","2030-09-05T10:10:00Z",4200,"1000000004","[email protected]","2030-09-09T08:31:00Z"
      "1006","2030-09-04T14:55:00Z",2800,"1000000005","[email protected]","2030-09-09T08:31:00Z"
      "1007","2030-09-03T21:05:00Z",1900,"1000000006","[email protected]","2030-09-09T08:31:00Z"
      "1008","2030-09-02T17:40:00Z",3600,"1000000007","[email protected]","2030-09-09T08:31:00Z"
      "1009","2030-09-01T09:25:00Z",3100,"1000000008","[email protected]","2030-09-09T08:31:00Z"
      "1010","2030-08-31T22:50:00Z",2700,"1000000009","[email protected]","2030-09-09T08:31:00Z"
  - type: csv
    model: line_items
    description: An example list of line items.
    data: |
      lines_item_id,order_id,sku
      "LI-1","1001","5901234123457"
      "LI-2","1001","4001234567890"
      "LI-3","1002","5901234123457"
      "LI-4","1002","2001234567893"
      "LI-5","1003","4001234567890"
      "LI-6","1003","5001234567892"
      "LI-7","1004","5901234123457"
      "LI-8","1005","2001234567893"
      "LI-9","1005","5001234567892"
      "LI-10","1005","6001234567891"
servicelevels:
  availability:
    description: The server is available during support hours
    percentage: 99.9%
  retention:
    description: Data is retained for one year
    period: P1Y
    unlimited: false
  latency:
    description: Data is available within 25 hours after the order was placed
    threshold: 25h
    sourceTimestampField: orders.order_timestamp
    processedTimestampField: orders.processed_timestamp
  freshness:
    description: The age of the youngest row in a table.
    threshold: 25h
    timestampField: orders.order_timestamp
  frequency:
    description: Data is delivered once a day
    type: batch # or streaming
    interval: daily # for batch, either or cron
    cron: 0 0 * * * # for batch, either or interval
  support:
    description: The data is available during typical business hours at headquarters
    time: 9am to 5pm in EST on business days
    responseTime: 1h
  backup:
    description: Data is backed up once a week, every Sunday at 0:00 UTC.
    interval: weekly
    cron: 0 0 * * 0
    recoveryTime: 24 hours
    recoveryPoint: 1 week
quality:
  type: SodaCL   # data quality check format: SodaCL, montecarlo, custom
  specification: # expressed as string or inline yaml or via "$ref: checks.yaml"
    checks for orders:
      - row_count >= 5
      - duplicate_count(order_id) = 0
    checks for line_items:
      - values in (order_id) must exist in orders (order_id)
      - row_count >= 5

Data Contract CLI

The Data Contract CLI is a command line tool and Python library to lint, test, import and export data contracts.

Here is short example how to verify that your actual dataset matches the data contract:

pip3 install datacontract-cli
datacontract test https://datacontract.com/examples/orders-latest/datacontract.yaml

or, if you prefer Docker:

docker run datacontract/cli test https://datacontract.com/examples/orders-latest/datacontract.yaml

The Data Contract contains all required information to verify data:

The servers block has the connection details to the actual data set.
The models define the syntax, formats, and constraints.
The quality defined further quality checks.

The Data Contract CLI chooses the appropriate engine, formulates test cases, connects to the server, and executes the tests, based on the server type.

More information and configuration options on cli.datacontract.com.

IDE Integration

IntelliJ comes with a built-in YAML plugin which will show you autocompletions. For VS Code we recommend to install the YAML plugin. No additional configuration is required. Autocompletion is then enabled for files following these patterns:

datacontract.yaml
datacontract.yml
*-datacontract.yaml
*-datacontract.yml
*.datacontract.yaml
*.datacontract.yml
datacontract-*.yaml
datacontract-*.yml
**/datacontract/*.yml
**/datacontract/*.yaml
**/datacontracts/*.yml
**/datacontracts/*.yaml

Specification

Data Contract Object
Info Object
Contact Object
Server Object
Terms Object
Model Object
Field Object
Definition Object
Schema Object
Example Object
Service Level Object
Quality Object
Data Types
Specification Extensions

JSON Schema of the Data Contract Specification.

Data Contract Object

This is the root document.

It is RECOMMENDED that the root document be named: datacontract.yaml.

Field	Type	Description
dataContractSpecification	`string`	REQUIRED. Specifies the Data Contract Specification being used.
id	`string`	REQUIRED. An organization-wide unique technical identifier, such as a UUID, URN, slug, string, or number
info	Info Object	REQUIRED. Specifies the metadata of the data contract. May be used by tooling.
servers	Map[string, Server Object]	Specifies the servers of the data contract.
terms	Terms Object	Specifies the terms and conditions of the data contract.
models	Map[string, Model Object]	Specifies the logical data model.
definitions	Map[string, Definition Object]	Specifies definitions.
schema	Schema Object	Specifies the physical schema. The specification supports different schema format.
examples	Array of Example Objects	Specifies example data sets for the data model. The specification supports different example types.
servicelevels	Service Levels Object	Specifies the service level of the provided data
quality	Quality Object	Specifies the quality attributes and checks. The specification supports different quality check DSLs.

This object MAY be extended with Specification Extensions.

Info Object

Metadata and life cycle information about the data contract.

Field	Type	Description
title	`string`	REQUIRED. The title of the data contract.
version	`string`	REQUIRED. The version of the data contract document (which is distinct from the Data Contract Specification version or the Data Product implementation version).
status	`string`	The status of the data contract. Can be proposed, in development, active, retired.
description	`string`	A description of the data contract.
owner	`string`	The owner or team responsible for managing the data contract and providing the data.
contact	Contact Object	Contact information for the data contract.

This object MAY be extended with Specification Extensions.

Contact Object

Contact information for the data contract.

Field	Type	Description
name	`string`	The identifying name of the contact person/organization.
url	`string`	The URL pointing to the contact information. This MUST be in the form of a URL.
email	`string`	The email address of the contact person/organization. This MUST be in the form of an email address.

This object MAY be extended with Specification Extensions.

Server Object

The fields are dependent on the defined type.

Field	Type	Description
type	`string`	REQUIRED. The type of the data product technology that implements the data contract. Well-known server types are: `bigquery`, `s3`, `glue`, `redshift`, `azure`, `snowflake`, `databricks`, `postgres`, `oracle`, `kafka`, `pubsub`, `sftp`, `kinesis`, `local`
description	`string`	An optional string describing the server.

This object MAY be extended with Specification Extensions.

BigQuery Server Object

Field	Type	Description
type	`string`	`bigquery`
project	`string`	The GCP project name.
dataset	`string`

S3 Server Object

Field	Type	Description
type	`string`	`s3`
location	`string`	S3 URL, starting with `s3://`
endpointUrl	`string`	The server endpoint for S3-compatible servers, such as `https://minio.example.com`
format	`string`	Format of files, such as `parquet`, `delta`, `json`, `csv`
delimiter	`string`	(Only for format = `json`), how multiple json documents are delimited within one file, e.g., `new_line`, `array`

Example:

servers:
  production:
    type: s3
    location: s3://acme-orders-prod/orders/

AWS Glue Server Object

Field	Type	Description
type	`string`	`glue`
account	`string`	REQUIRED. The AWS account, e.g., `1234-5678-9012`
database	`string`	REQUIRED. The AWS Glue Catalog database
location	`string`	S3 path, starting with `s3://`
format	`string`	Format of files, such as `parquet`, `delta`, `json`, `csv`

Example:

servers:
  production:
    type: glue
    account: "1234-5678-9012"
    database: acme-orders
    location: s3://acme-orders-prod/orders/
    format: parquet

Redshift Server Object

Field	Type	Description
type	`string`	`redshift`
account	`string`
database	`string`
schema	`string`

Azure Server Object

Field	Type	Description
type	`string`	`azure`
location	`string`	Fully qualified path to Azure Blob Storage or Azure Data Lake Storage (ADLS), supports globs. Starting with `az://` or `abfss` Examples: `az://my_storage_account_name.blob.core.windows.net/my_container/path/.parquet` or `abfss://my_storage_account_name.dfs.core.windows.net/my_container_name/path/.parquet`
format	`string`	Format of files, such as `parquet`, `json`, `csv`
delimiter	`string`	(Only for format = `json`), how multiple json documents are delimited within one file, e.g., `new_line`, `array`

Snowflake Server Object

Field	Type	Description
type	`string`	`snowflake`
account	`string`
database	`string`
schema	`string`

Databricks Server Object

Field	Type	Description
type	`string`	`databricks`
host	`string`	The Databricks host, e.g., `dbc-abcdefgh-1234.cloud.databricks.com`
catalog	`string`	The name of the Hive or Unity catalog
schema	`string`	The schema name in the catalog

Postgres Server Object

Field	Type	Description
type	`string`	`postgres`
host	`string`	The host to the database server
port	`integer`	The port to the database server
database	`string`	The name of the database, e.g., `postgres`.
schema	`string`	The name of the schema in the database, e.g., `public`.

Oracle Server Object

Field	Type	Description
type	`string`	`oracle`
host	`string`	The host to the oracle server
port	`integer`	The port to the oracle server
serviceName	`string`	The name of the service

Kafka Server Object

Field	Type	Description
type	`string`	`kafka`
host	`string`	The bootstrap server of the kafka cluster.
topic	`string`	The topic name.
format	`string`	The format of the message. Examples: json, avro, protobuf. Default: json.

Pub/Sub Server Object

Field	Type	Description
type	`string`	`pubsub`
project	`string`	The GCP project name.
topic	`string`	The topic name.

sftp Server Object

Field	Type	Description
type	`string`	`sftp`
location	`string`	S3 URL, starting with `sftp://`
format	`string`	Format of files, such as `parquet`, `delta`, `json`, `csv`
delimiter	`string`	(Only for format = `json`), how multiple json documents are delimited within one file, e.g., `new_line`, `array`

AWS Kinesis Data Streams Server Object

Field	Type	Description
type	`string`	`kinesis`
stream	`string`	The name of the Kinesis data stream.
region	`string`	AWS region, e.g., `eu-west-1`.
format	`string`	The format of the records. Examples: json, avro, protobuf.

Local Server Object

Field	Type	Description
type	`string`	`local`
path	`string`	The relative or absolute path to the data file(s), such as `./folder/data.parquet`.
format	`string`	The format of the file(s), such as `parquet`, `delta`, `csv`, or `json`.

Terms Object

The terms and conditions of the data contract.

Field	Type	Description
usage	`string`	The usage describes the way the data is expected to be used. Can contain business and technical information.
limitations	`string`	The limitations describe the restrictions on how the data can be used, can be technical or restrictions on what the data may not be used for.
billing	`string`	The billing describes the pricing model for using the data, such as whether it's free, having a monthly fee, or metered pay-per-use.
noticePeriod	`string`	The period of time that must be given by either party to terminate or modify a data usage agreement. Uses ISO-8601 period format, e.g., `P3M` for a period of three months.

Model Object

The Model Object describes the structure and semantics of a data model, such as tables, views, or structured files.

The name of the data model (table name) is defined by the key that refers to this Model Object.

Field	Type	Description
type	`string`	The type of the model. Examples: `table`, `view`, `object`. Default: `table`.
description	`string`	An optional string describing the data model.
title	`string`	An optional string for the title of the data model. Especially useful if the name of the model is cryptic or contains abbreviations.
fields	Map[`string`, Field Object]	The fields (e.g. columns) of the data model.

Field Object

The Field Objects describes one field (column, property, nested field) of a data model.

Field	Type	Description
description	`string`	An optional string describing the semantic of the data in this field.
type	Data Type	The logical data type of the field.
title	`string`	An optional string providing a human readable name for the field. Especially useful if the field name is cryptic or contains abbreviations.
enum	array of `string`	A value must be equal to one of the elements in this array value. Only evaluated if the value is not null.
required	`boolean`	An indication, if this field must contain a value and may not be null. Default: `false`
primary	`boolean`	If this field is a primary key. Default: `false`
references	`string`	The reference to a field in another model. E.g. use 'orders.order_id' to reference the order_id field of the model orders. Think of defining a foreign key relationship.
unique	`boolean`	An indication, if the value must be unique within the model. Default: `false`
format	`string`	`email`: A value must be complaint to RFC 5321, section 4.1.2. `uri`: A value must be complaint to RFC 3986. `uuid`: A value must be complaint to RFC 4122. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
precision	`number`	The maximum number of digits in a number. Only applies to numeric values. Defaults to 38.
scale	`number`	The maximum number of decimal places in a number. Only applies to numeric values. Defaults to 0.
minLength	`number`	A value must greater than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
maxLength	`number`	A value must less than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
pattern	`string`	A value must be valid according to the ECMA-262 regular expression dialect. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
minimum	`number`	A value of a number must greater than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to numeric values.
exclusiveMinimum	`number`	A value of a number must greater than the value of this. Only evaluated if the value is not null. Only applies to numeric values.
maximum	`number`	A value of a number must less than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to numeric values.
exclusiveMaximum	`number`	A value of a number must less than the value of this. Only evaluated if the value is not null. Only applies to numeric values.
example	`string`	An example value.
pii	`boolean`	An indication, if this field contains Personal Identifiable Information (PII).
classification	`string`	The data class defining the sensitivity level for this field, according to the organization's classification scheme. Examples may be: `sensitive`, `restricted`, `internal`, `public`.
tags	Array of `string`	Custom metadata to provide additional context.
$ref	`string`	A reference URI to a definition in the specification, internally or externally. Properties will be inherited from the definition.
fields	Map[`string`, Field Object]	The nested fields (e.g. columns) of the object, record, or struct. Use only when type is object, record, or struct.
items	Field Object	The type of the elements in the array. Use only when type is array.

Definition Object

The Definition Object includes a clear and concise explanations of syntax, semantic, and classification of a business object in a given domain. It serves as a reference for a common understanding of terminology, ensure consistent usage and to identify join-able fields. Models fields can refer to definitions using the $ref field to link to existing definitions and avoid duplicate documentations.

Field	Type	Description
name	`string`	REQUIRED. The technical name of this definition.
type	Data Type	REQUIRED. The logical data type
domain	`string`	The domain in which this definition is valid. Default: `global`.
title	`string`	The business name of this definition.
description	`string`	Clear and concise explanations related to the domain
enum	array of `string`	A value must be equal to one of the elements in this array value. Only evaluated if the value is not null.
format	`string`	`email`: A value must be complaint to RFC 5321, section 4.1.2. `uri`: A value must be complaint to RFC 3986. `uuid`: A value must be complaint to RFC 4122. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
precision	`number`	The maximum number of digits in a number. Only applies to numeric values. Defaults to 38.
scale	`number`	The maximum number of decimal places in a number. Only applies to numeric values. Defaults to 0.
minLength	`number`	A value must greater than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
maxLength	`number`	A value must less than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
pattern	`string`	A value must be valid according to the ECMA-262 regular expression dialect. Only evaluated if the value is not null. Only applies to unicode character sequences types (`string`, `text`, `varchar`).
minimum	`number`	A value of a number must greater than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to numeric values.
exclusiveMinimum	`number`	A value of a number must greater than the value of this. Only evaluated if the value is not null. Only applies to numeric values.
maximum	`number`	A value of a number must less than, or equal to, the value of this. Only evaluated if the value is not null. Only applies to numeric values.
exclusiveMaximum	`number`	A value of a number must less than the value of this. Only evaluated if the value is not null. Only applies to numeric values.
example	`string`	An example value.
pii	`boolean`	An indication, if this field contains Personal Identifiable Information (PII).
classification	`string`	The data class defining the sensitivity level for this field, according to the organization's classification scheme.
tags	Array of `string`	Custom metadata to provide additional context.

Schema Object

The schema of the data contract describes the physical schema. The type of the schema depends on the data platform.

Field	Type	Description
type	`string`	REQUIRED. The type of the schema. Typical values are: `dbt`, `bigquery`, `json-schema`, `sql-ddl`, `avro`, `protobuf`, `custom`
specification	dbt Schema Object \| BigQuery Schema Object \| JSON Schema Schema Object \| SQL DDL Schema Object \| `string`	REQUIRED. The specification of the schema. The schema specification can be encoded as a string or as inline YAML.

dbt Schema Object

https://docs.getdbt.com/reference/model-properties

Example (inline YAML):

schema:
  type: dbt
  specification:
    version: 2
    models:
      - name: "My Table"
        description: "My description"
        columns:
          - name: "My column"
            data_type: text
            description: "My description"

Example (string):

schema:
  type: dbt
  specification: |-
    version: 2
    models:
      - name: "My Table"
        description: "My description"
        columns:
          - name: "My column"
            data_type: text
            description: "My description"

BigQuery Schema Object

The schema structure is defined by the Google BigQuery Table object. You can extract such a Table object via the tables.get endpoint.

Instead of providing a single Table object, you can also provide an array of such objects. Be aware that tables.list only returns a subset of the full Table object. You need to call every Table object via tables.get to get the full Table object, including the actual schema.

Learn more: Google BigQuery REST Reference v2

Example:

schema:
  type: bigquery
  specification: |-
    {
      "tableReference": {
        "projectId": "my-project",
        "datasetId": "my_dataset",
        "tableId": "my_table"
      },
      "description": "This is a description",
      "type": "TABLE",
      "schema": {
        "fields": [
          {
            "name": "name",
            "type": "STRING",
            "mode": "NULLABLE",
            "description": "This is a description"
          }
        ]
      }
    }

JSON Schema Schema Object

JSON Schema can be defined as JSON or rendered as YAML, following the OpenAPI Schema Object dialect

Example (inline YAML):

schema:
  type: json-schema
  specification:
    orders:
      description: One record per order. Includes cancelled and deleted orders.
      type: object
      properties:
        order_id:
          type: string
          description: Primary key of the orders table
        order_timestamp:
          type: string
          format: date-time
          description: The business timestamp in UTC when the order was successfully registered in the source system and the payment was successful.
        order_total:
          type: integer
          description: Total amount of the order in the smallest monetary unit (e.g., cents).
    line_items:
      type: object
      properties:
        lines_item_id:
          type: string
          description: Primary key of the lines_item_id table
        order_id:
          type: string
          description: Foreign key to the orders table
        sku:
          type: string
          description: The purchased article number

Example (string):

schema:
  type: json-schema
  specification: |-
    {
      "$schema": "http://json-schema.org/draft-07/schema#",
      "type": "object",
      "properties": {
        "orders": {
          "type": "object",
          "description": "One record per order. Includes cancelled and deleted orders.",
          "properties": {
            "order_id": {
              "type": "string",
              "description": "Primary key of the orders table"
            },
            "order_timestamp": {
              "type": "string",
              "format": "date-time",
              "description": "The business timestamp in UTC when the order was successfully registered in the source system and the payment was successful."
            },
            "order_total": {
              "type": "integer",
              "description": "Total amount of the order in the smallest monetary unit (e.g., cents)."
            }
          },
          "required": ["order_id", "order_timestamp", "order_total"]
        },
        "line_items": {
          "type": "object",
          "properties": {
            "lines_item_id": {
              "type": "string",
              "description": "Primary key of the lines_item_id table"
            },
            "order_id": {
              "type": "string",
              "description": "Foreign key to the orders table"
            },
            "sku": {
              "type": "string",
              "description": "The purchased article number"
            }
          },
          "required": ["lines_item_id", "order_id", "sku"]
        }
      },
      "required": ["orders", "line_items"]
    }

SQL DDL Schema Object

Classical SQL DDLs can be used to describe the structure.

Example (string):

schema:
  type: sql-ddl
  specification: |-
      -- One record per order. Includes cancelled and deleted orders.
      CREATE TABLE orders (
        order_id TEXT PRIMARY KEY, -- Primary key of the orders table
        order_timestamp TIMESTAMPTZ NOT NULL, -- The business timestamp in UTC when the order was successfully registered in the source system and the payment was successful.
        order_total INTEGER NOT NULL -- Total amount of the order in the smallest monetary unit (e.g., cents)
      );
    
      -- The items that are part of an order
      CREATE TABLE line_items (
        lines_item_id TEXT PRIMARY KEY, -- Primary key of the lines_item_id table
        order_id TEXT REFERENCES orders(order_id), -- Foreign key to the orders table
        sku TEXT NOT NULL -- The purchased article number
      );

Example Object

Field	Type	Description
type	`string`	The type of the data product technology that implements the data contract. Well-known server types are: `csv`, `json`, `yaml`, `custom`
description	`string`	An optional string describing the example.
model	`string`	The reference to the model in the schema, e.g. a table name.
data	`string`	Example data for this model.

Example:

examples:
- type: csv
  model: orders
  data: |-
    order_id,order_timestamp,order_total
    "1001","2023-09-09T08:30:00Z",2500
    "1002","2023-09-08T15:45:00Z",1800
    "1003","2023-09-07T12:15:00Z",3200
    "1004","2023-09-06T19:20:00Z",1500
    "1005","2023-09-05T10:10:00Z",4200
    "1006","2023-09-04T14:55:00Z",2800
    "1007","2023-09-03T21:05:00Z",1900
    "1008","2023-09-02T17:40:00Z",3600
    "1009","2023-09-01T09:25:00Z",3100
    "1010","2023-08-31T22:50:00Z",2700

Service Levels Object

A service level is defined as an agreed-upon, measurable level of performance for provided the data. Data Contract Specification defines well-known service levels. This list can be extended with custom service levels.

One can either describe each service level informally using the description field, or make use of the predefined fields for automation support, e.g., via the Data Contract CLI.

Field	Type	Description
availability	Availability Object	The promised uptime of the system that provides the data
retention	Retention Object	The period how long data will be available.
latency	Latency Object	The maximum amount of time from the from the source to its destination.
freshness	Freshness Object	The maximum age of the youngest entry.
frequency	Frequency Object	The update frequency.
support	Support Object	The times when support is provided.
backup	Backup Object	The details about data backup procedures.

This object MAY be extended with Specification Extensions.

Availability Object

Availability refers to the promise or guarantee by the service provider about the uptime of the system that provides the data.

Field	Type	Description
description	`string`	An optional string describing the availability service level.
percentage	`string`	An optional string describing the guaranteed uptime in percent (e.g., `99.9%`)

This object MAY be extended with Specification Extensions.

Retention Object

Retention covers the period how long data will be available.

Field	Type	Description
description	`string`	An optional string describing the retention service level.
period	`string`	An optional period of time, how long data is available. Supported formats: Simple duration (e.g., `1 year`, `30d`) and ISO 8601 duration (e.g, `P1Y`).
unlimited	`boolean`	An optional indicator that data is kept forever.
timestampField	`string`	An optional reference to the field that contains the timestamp that the period refers to.

This object MAY be extended with Specification Extensions.

Latency Object

Latency refers to the maximum amount of time from the source to its destination.

Examples are the maximum duration it takes after an order has been recorded in the ecommerce shop until it is available in the orders table in the data analytics platform. This includes the waiting times until the next batch run is started and the processing time of the pipeline.

Field	Type	Description
description	`string`	An optional string describing the latency service level.
threshold	`string`	An optional maximum duration between the source timestamp and the processed timestamp. Supported formats: Simple duration (e.g., `24 hours`, `5s`) and ISO 8601 duration (e.g, `PT24H`).
sourceTimestampField	`string`	An optional reference to the field that contains the timestamp when the data was provided at the source.
processedTimestampField	`string`	An optional reference to the field that contains the processing timestamp, which denotes when the data is made available to consumers of this data contract.

This object MAY be extended with Specification Extensions.

Freshness Object

Freshness refers to the maximum age of the youngest entry.

Field	Type	Description
description	`string`	An optional string describing the freshness service level.
threshold	`string`	An optional maximum age of the youngest entry. Supported formats: Simple duration (e.g., `24 hours`, `5s`) and ISO 8601 duration (e.g, `PT24H`).
timestampField	`string`	An optional reference to the field that contains the timestamp that the threshold refers to.

This object MAY be extended with Specification Extensions.

Frequency Object

Frequency describes how often data is updated.

Field	Type	Description
description	`string`	An optional string describing the frequency service level.
type	`string`	An optional type of data processing. Typical values are `batch`, `micro-batching`, `streaming`, `manual`.
interval	`string`	Optional. Only for batch: How often the pipeline is triggered, e.g., `daily`.
cron	`string`	Optional. Only for batch: A cron expression when the pipelines is triggered. E.g., `0 0 * * *`.

This object MAY be extended with Specification Extensions.

Support Object

Support describes the times when support will be available for contact.

Field	Type	Description
description	`string`	An optional string describing the support service level.
time	`string`	An optional string describing the times when support will be available for contact such as `24/7` or `business hours only`.
responseTime	`string`	An optional string describing the time it takes for the support team to acknowledge a request. This does not mean the issue will be resolved immediately, but it assures users that their request has been received and will be dealt with.

This object MAY be extended with Specification Extensions.

Backup Object

Backup specifies details about data backup procedures.

Field	Type	Description
description	`string`	An optional string describing the backup service level.
interval	`string`	An optional interval that defines how often data will be backed up, e.g., `daily`.
cron	`string`	An optional cron expression when data will be backed up, e.g., `0 0 * * *`.
recoveryTime	`string`	An optional Recovery Time Objective (RTO) specifies the maximum amount of time allowed to restore data from a backup after a failure or loss event (e.g., 4 hours, 24 hours).
recoveryPoint	`string`	An optional Recovery Point Objective (RPO) defines the maximum acceptable age of files that must be recovered from backup storage for normal operations to resume after a disaster or data loss event. This essentially measures how much data you can afford to lose, measured in time (e.g., 4 hours, 24 hours).

Quality Object

The quality object contains quality attributes and checks.

Field	Type	Description
type	`string`	REQUIRED. The type of the schema. Typical values are: `SodaCL`, `montecarlo`, `great-expectations`, `custom`
specification	SodaCL Quality Object \| Monte Carlo Schema Object \| `string`	REQUIRED. The specification of the quality attributes. The quality specification can be encoded as a string or as inline YAML.

SodaCL Quality Object

Quality attributes in Soda Checks Language.

The specification represents the content of a checks.yml file.

Example (inline):

quality:
  type: SodaCL   # data quality check format: SodaCL, montecarlo, dbt-tests, custom
  specification: # expressed as string or inline yaml or via "$ref: checks.yaml"
    checks for orders:
      - row_count > 0
      - duplicate_count(order_id) = 0
    checks for line_items:
      - row_count > 0

Example (string):

quality:
  type: SodaCL
  specification: |-
    checks for search_queries:
      - freshness(search_timestamp) < 1d
      - row_count > 100000
      - missing_count(search_query) = 0

Monte Carlo Quality Object

Quality attributes defined as Monte Carlos Monitors as Code.

The specification represents the content of a montecarlo.yml file.

Example (string):

quality:
  type: montecarlo
  specification: |-
    montecarlo:
      field_health:
        - table: project:dataset.table_name
          timestamp_field: created
      dimension_tracking:
        - table: project:dataset.table_name
          timestamp_field: created
          field: order_status

Great Expectations Quality Object

Quality attributes defined as Great Expectations Expectations.

The specification represents a list of expectations on a specific model.

Example (string):

quality:
  type: great-expectations
  specification:
    orders: |-
      [
          {
              "expectation_type": "expect_table_row_count_to_be_between",
              "kwargs": {
                  "min_value": 10
              },
              "meta": {
      
              }
          }
      ]

Data Types

The following data types are supported for model fields and definitions:

Unicode character sequence: string, text, varchar
Any numeric type, either integers or floating point numbers: number, decimal, numeric
32-bit signed integer: int, integer
64-bit signed integer: long, bigint
Single precision (32-bit) IEEE 754 floating-point number: float
Double precision (64-bit) IEEE 754 floating-point number: double
Binary value: boolean
Timestamp with timezone: timestamp, timestamp_tz
Timestamp with no timezone: timestamp_ntz
Date with no time information: date
Array: array
Sequence of 8-bit unsigned bytes: bytes
Complex type: object, record, struct
No value: null

Specification Extensions

While the Data Contract Specification tries to accommodate most use cases, additional data can be added to extend the specification at certain points.

A custom fields can be added with any name. The value can be null, a primitive, an array or an object.

Design Principles

The Data Contract Specification follows these design principles:

A free, open, and open-sourced standard
Follow OpenAPI and AsyncAPI conventions so that it feels immediately familiar
Support contract-first approaches
Support code-first approaches
Support tooling by being machine-readable

Tooling

Data Contract CLI is a free CLI tool to help you create, develop, and maintain your data contracts.
Data Mesh Manager is a commercial tool to manage data products and data contracts. It supports the data contract specification and allows the user to import or export data contracts using this specification.

Other Data Contract Specifications

Literature

Driving Data Quality with Data Contracts by Andrew Jones

Authors

The Data Contract Specification was originally created by Jochen Christ and Dr. Simon Harrer, and is currently maintained by them.

Contributing

Contributions are welcome! Please open an issue or a pull request.

License

MIT License

Name		Name	Last commit message	Last commit date
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.github		.github
_layouts		_layouts
diagrams		diagrams
examples		examples
images		images
versions		versions
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CNAME		CNAME
LICENSE		LICENSE
README.md		README.md
_config.yml		_config.yml
datacontract.init.yaml		datacontract.init.yaml
datacontract.schema.json		datacontract.schema.json
definition.schema.json		definition.schema.json
gen-openapi-yaml		gen-openapi-yaml
workshop.md		workshop.md

License

northvolt/datacontract-specification

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Data Contract Specification

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Data Contract Object

Info Object

Contact Object

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Redshift Server Object

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dbt Schema Object

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JSON Schema Schema Object

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Service Levels Object

Availability Object

Retention Object

Latency Object

Freshness Object

Frequency Object

Support Object

Backup Object

Quality Object

SodaCL Quality Object

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Great Expectations Quality Object

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