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Data Contract Specification

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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. Think of an API, but for data. A data contract is implemented by a data product or other data technologies, even legacy data warehouses. 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.

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 by the industry. 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

1.1.0(Changelog)

Example

View in Data Contract Catalog

dataContractSpecification: 1.1.0
id: urn:datacontract:checkout:orders-latest
info:
  title: Orders Latest
  version: 2.0.0
  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
    environment: prod
    location: s3://datacontract-example-orders-latest/v2/{model}/*.json
    format: json
    delimiter: new_line
    description: "One folder per model. One file per day."
    roles:
      - name: analyst_us
        description: Access to the data for US region
      - name: analyst_cn
        description: Access to the data for China region
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
  policies:
    - name: privacy-policy
      url: https://example.com/privacy-policy
    - name: license
      description: External data is licensed under agreement 1234.
      url: https://example.com/license/1234
  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
        primaryKey: 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
        examples:
          - "2024-09-09T08:30:00Z"
        tags: ["business-timestamp"]
      order_total:
        description: Total amount the smallest monetary unit (e.g., cents).
        type: long
        required: true
        examples:
          - 9999
        quality:
          - type: sql
            description: 95% of all order total values are expected to be between 10 and 499 EUR.
            query: |
              SELECT quantile_cont(order_total, 0.95) AS percentile_95
              FROM orders
            mustBeBetween: [1000, 49900]
      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.
        type: text
        format: email
        required: true
        pii: true
        classification: sensitive
        quality:
          - type: text
            description: The email address is not verified and may be invalid.
        lineage:
          inputFields:
            - namespace: com.example.service.checkout
              name: checkout_db.orders
              field: email_address
      processed_timestamp:
        description: The timestamp when the record was processed by the data platform.
        type: timestamp
        required: true
        config:
          jsonType: string
          jsonFormat: date-time
    quality:
      - type: sql
        description: The maximum duration between two orders should be less that 3600 seconds
        query: |
          SELECT MAX(EXTRACT(EPOCH FROM (order_timestamp - LAG(order_timestamp) OVER (ORDER BY order_timestamp)))) AS max_duration
          FROM orders
        mustBeLessThan: 3600
      - type: sql
        description: Row Count
        query: |
          SELECT count(*) as row_count
          FROM orders
        mustBeGreaterThan: 5
    examples:
      - |
        order_id,order_timestamp,order_total,customer_id,customer_email_address,processed_timestamp
        "1001","2030-09-09T08:30:00Z",2500,"1000000001","mary.taylor82@example.com","2030-09-09T08:31:00Z"
        "1002","2030-09-08T15:45:00Z",1800,"1000000002","michael.miller83@example.com","2030-09-09T08:31:00Z"
        "1003","2030-09-07T12:15:00Z",3200,"1000000003","michael.smith5@example.com","2030-09-09T08:31:00Z"
        "1004","2030-09-06T19:20:00Z",1500,"1000000004","elizabeth.moore80@example.com","2030-09-09T08:31:00Z"
        "1005","2030-09-05T10:10:00Z",4200,"1000000004","elizabeth.moore80@example.com","2030-09-09T08:31:00Z"
        "1006","2030-09-04T14:55:00Z",2800,"1000000005","john.davis28@example.com","2030-09-09T08:31:00Z"
        "1007","2030-09-03T21:05:00Z",1900,"1000000006","linda.brown67@example.com","2030-09-09T08:31:00Z"
        "1008","2030-09-02T17:40:00Z",3600,"1000000007","patricia.smith40@example.com","2030-09-09T08:31:00Z"
        "1009","2030-09-01T09:25:00Z",3100,"1000000008","linda.wilson43@example.com","2030-09-09T08:31:00Z"
        "1010","2030-08-31T22:50:00Z",2700,"1000000009","mary.smith98@example.com","2030-09-09T08:31:00Z"
  line_items:
    description: A single article that is part of an order.
    type: table
    fields:
      line_item_id:
        type: text
        description: Primary key of the lines_item_id table
        required: true
      order_id:
        $ref: '#/definitions/order_id'
        references: orders.order_id
      sku:
        description: The purchased article number
        $ref: '#/definitions/sku'
    primaryKey: ["order_id", "line_item_id"]
    examples:
      - |
        line_item_id,order_id,sku
        "LI-1","1001","5901234123457"
        "LI-2","1001","4001234567890"
        "LI-3","1002","5901234123457"
        "LI-4","1002","2001234567893"
        "LI-5","1003","4001234567890"
        "LI-6","1003","5001234567892"
        "LI-7","1004","5901234123457"
        "LI-8","1005","2001234567893"
        "LI-9","1005","5001234567892"
        "LI-10","1005","6001234567891"
definitions:
  order_id:
    title: Order ID
    type: text
    format: uuid
    description: An internal ID that identifies an order in the online shop.
    examples:
      - 243c25e5-a081-43a9-aeab-6d5d5b6cb5e2
    pii: true
    classification: restricted
    tags:
      - orders
  sku:
    title: Stock Keeping Unit
    type: text
    pattern: ^[A-Za-z0-9]{8,14}$
    examples:
      - "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.
    links:
      wikipedia: https://en.wikipedia.org/wiki/Stock_keeping_unit
    tags:
      - inventory
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
tags:
  - checkout
  - orders
  - s3
links:
  datacontractCli: https://cli.datacontract.com

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.

Specification

The eight major categories in the data contract specification

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.
servicelevels Service Levels Object Specifies the service level of the provided data
links Map[string, string] Additional external documentation links.
tags Array of string Custom metadata to provide additional context.

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, deprecated, 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, sqlserver, snowflake, databricks, postgres, oracle, kafka, pubsub, sftp, kinesis, trino, local
description string An optional string describing the server.
environment string An optional string describing the environment, e.g., prod, sit, stg.
roles Array of Server Role Object An optional array of roles that are available and can be requested to access the server for role-based access control. E.g. separate roles for different regions or sensitive data.

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 MioIO or Google Cloud Storage, e.g., 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 (AWS S3):

servers:
  production:
    type: s3
    location: s3://acme-orders-prod/orders/
    format: json
    delimiter: new_line

Example (MinIO):

servers:
  minio:
    type: s3
    endpointUrl: http://localhost:9000
    location: s3://my-bucket/path/
    format: delta

Example (Google Cloud Storage):

servers:
  gcs:
    type: s3
    endpointUrl: https://storage.googleapis.com
    location: s3://my-bucket/path/*/*/*/*/*.parquet
    format: parquet

Redshift Server Object

Field Type Description
type string redshift
account string
database string
schema string
clusterIdentifier string Identifier of the cluster.
Example: analytics-cluster
host string Host of the cluster.
Example: analytics-cluster.example.eu-west-1.redshift.amazonaws.com
port number Port of the cluster.
Example: 5439
endpoint string Endpoint of the cluster
Example: analytics-cluster.example.eu-west-1.redshift.amazonaws.com:5439/analytics

Example, specifying an endpoint:

servers:
  analytics:
    type: redshift
    account: '123456789012'
    database: analytics
    schema: analytics
    endpoint: analytics-cluster.example.eu-west-1.redshift.amazonaws.com:5439/analytics

Example, specifying the cluster identifier:

servers:
  analytics:
    type: redshift
    account: '123456789012'
    database: analytics
    schema: analytics
    clusterIdentifier: analytics-cluster

Example, specifying the cluster host:

servers:
  analytics:
    type: redshift
    account: '123456789012'
    database: analytics
    schema: analytics
    host: analytics-cluster.example.eu-west-1.redshift.amazonaws.com
    port: 5439

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

SQL-Server Server Object

Field Type Description
type string sqlserver
host string The host to the database server
port integer The port to the database server, default: 1433
database string The name of the database, e.g., database.
schema string The name of the schema in the database, e.g., dbo.
driver string The name of the supported driver, e.g., ODBC Driver 18 for SQL Server.

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.

Trino Server Object

Field Type Description
type string trino
host string The Trino host
port integer The Trino port
catalog string The name of the catalog, e.g., my_catalog.
schema string The name of the schema in the catalog, e.g., my_schema.

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.

Server Role Object

Field Type Description
name string Name of the role
description string A description of the role and what access the role provides.

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.
policies Array of Policy Object A list of policies, licenses, standards, that are applicable for this data contract and that must be acknowledged by data consumers.
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.

This object MAY be extended with Specification Extensions.

Policy Object

Field Type Description
name string Name of the policy.
description string A description of the policy.
url string An URL that refers to the policy.

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.
primaryKey Array of string If the primary key is a compound key, list the field names that constitute the primary key. Alternative to field-level primaryKey.
quality Array of Quality Object Specifies the quality attributes on model level.
examples Array of Any Specifies example data sets for the model.
config Config Object Any additional key-value pairs that might be useful for further tooling.

This object MAY be extended with Specification Extensions.

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
primaryKey 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 DEPRECATED, use examples. An example value.
examples Array of Any A list of example values.
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.
links Map[string,string] Additional external documentation links.
$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.
keys Field Object Describes the key structure of a map. Defaults to type: string if a map is defined as type. Not all server types support different key types. Use only when type is map.
values Field Object Describes the value structure of a map. Use only when type is map.
quality Array of Quality Object Specifies the quality attributes on field level.
lineage Lineage Object Provides information where the data comes from.
config Config Object Any additional key-value pairs that might be useful for further tooling.

This object MAY be extended with Specification Extensions.

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
type Data Type REQUIRED. The logical data type
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.
examples Array of Any A list of example values.
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.
links Map[string, string] Additional external documentation links.
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.
keys Field Object Describes the key structure of a map. Defaults to type: string if a map is defined as type. Not all server types support different key types. Use only when type is map.
values Field Object Describes the value structure of a map. Use only when type is map.

This object MAY be extended with Specification Extensions.

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 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 defines quality attributes.

Quality attributes are checks that can be applied to the data to ensure its quality. Data can be verified by executing these checks through a data quality engine.

Quality attributes can be:

  • A text in natural language that describes the quality of the data.
  • An individual SQL query that returns a single value that can be compared.
  • Engine-specific types: Pre-defined quality checks, as defined by data quality libraries. Currently, the engines soda and great-expectations are supported.

A quality object can be specified on field level and on model level. The top-level quality object is deprecated.

Description Text

A description in natural language that defines the expected quality of the data. This is useful to express requirements or expectation when discussing the data contract with stakeholders. Later in the development process, these might be translated into an executable check (such as sql). It can also be used as a prompt to check the data with an AI engine.

Field Type Description
type string text
description string A plain text describing the quality attribute in natural language.

Example:

models:
  my_table:
    fields:
      account_iban:
        quality:
          - type: text
            description: Must be a valid IBAN. Must not be empty.

SQL

An individual SQL query that returns a single number that can be compared with a threshold. The SQL query must be in the SQL dialect of the provided server.

Note: Establish a secure development process and use read-only connections, as the misuse of SQL queries can lead to SQL injection attacks.

Field Type Description
type string sql
description string A plain text describing the quality of the data.
query string A SQL query that returns a single number to compare with the threshold.
dialect string The SQL dialect that is used for the query. Should be compatible to the server type. Examples: postgres, spark, bigquery, snowflake, duckdb, ...
mustBe integer The threshold to check the return value of the query
mustNotBe integer The threshold to check the return value of the query
mustBeGreaterThan integer The threshold to check the return value of the query
mustBeGreaterThanOrEqualTo integer The threshold to check the return value of the query
mustBeLessThan integer The threshold to check the return value of the query
mustBeLessThanOrEqualTo integer The threshold to check the return value of the query
mustBeBetween array of two integers The threshold to check the return value of the query. Boundaries are inclusive.
mustNotBeBetween array of two integers The threshold to check the return value of the query. Boundaries are inclusive.

In the query the following placeholders can be used:

Placeholder Description
{model} The name of the model that is checked.
{table} Alias for {model}.
{field} The name of the field that is checked (only if the quality is defined on field-level).
{column} Alias for {field}.

Example:

models:
  orders:
    quality:
      - type: sql
        description: The maximum duration between two orders must be less that 3600 seconds
        query: |
          SELECT MAX(EXTRACT(EPOCH FROM (order_timestamp - LAG(order_timestamp) OVER (ORDER BY order_timestamp)))) AS max_duration
          FROM {model}
        mustBeLessThan: 3600

SQL queries allow powerful checks for custom business logic. A SQL query should run not longer than 10 minutes.

Custom

You can define custom quality attributes that are specific to a data quality engine.

Custom (Engine: Soda)

Soda has a number of predefined quality checks that can be referenced as quality attributes.

Soda checks can be applied on model and field level.

Note: Soda Data contract check reference is experimental and may change in the future. Currently only supported by Postgres, Snowflake, and Spark (Databricks)

Field Type Description
type string custom
description string Optional. A plain text describing the quality attribute in natural language.
engine string soda
implementation object A check type as defined in the Data contract check reference

See the Data contract check reference for all possible types and configuration values.

Example:

models:
  my_table:
    fields:
      order_id:
        type: string
        quality:
          - type: custom
            description: This is a check on field level
            engine: soda
            implementation:
              type: no_duplicate_values
      carrier:
        type: string
      shipment_numer:
        type: string
    quality:
      - type: custom
        description: This is a check on model level
        engine: soda
        implementation:
          type: duplicate_percent
          columns:
            - carrier
            - shipment_numer
          must_be_less_than: 1.0
      - type: custom
        description: This is a check on model level
        engine: soda
        implementation:
          type: row_count
          must_be_greater_than: 500000

Custom (Engine: Great Expectations)

Quality attributes defined as Great Expectations Expectation.

Expectations are applied on model level.

Field Type Description
description string Optional. A plain text describing the quality attribute in natural language.
engine string great-expectations
implementation object An expectation type as listed in Expectation as YAML.

Example:

models:
  my_table:
    quality:
      - type: custom
        engine: great-expectations
        implementation:
          expectation_type: expect_table_row_count_to_be_between
          kwargs:
            min_value: 10000
            max_value: 50000
          meta:
            notes: "This expectation is crucial to avoid processing datasets that are too small or too large."
      - type: custom
        engine: great-expectations
        description: "Check that passenger_count values are between 1 and 6."
        implementation:
          expectation_type: expect_column_values_to_be_between
          kwargs:
            column: passenger_count
            max_value: 6
            min_value: 1
            mostly: 1.0
            strict_max: false
            strict_min: false
          meta:
            tags:
              - business-critical
              - range_check

Lineage Object

Field level lineage provides optional fine-grained information where the data comes from and how it was transformed.

The lineage object is based on the OpenLinage Column Level Lineage Dataset Facet to describe the input fields.

Field Type Description
inputFields Array of InputField Object The input fields refer to specific fields, columns, or data points from source systems or other data contracts that feed into a particular transformation, calculation, or final result.

InputField Object

Field Type Description
namespace string The input dataset namespace, such as the name of the source system or the domain of another data contract. Examples: com.example.crm, checkout, snowflake://{account name}. More on namespace
name string The input dataset name, such as a reference to a data contract, a fully qualified table name, a Kafka topic.
field string The input field name, such as the field in an upstream data contract, a table column or a JSON Path.
transformations Array of Transformation Object Optional. This describes how the input field data was used to generate the final result.

Transformation Object

Field Type Description
type string Indicates how direct is the relationship e.g. in query. Allows values are: DIRECT and INDIRECT.
subtype string Optional. Contains more specific information about the transformation.
Allowed values for type DIRECT: IDENTITY, TRANSFORMATION, AGGREGATION.
Allowed values for type INDIRECT: JOIN, GROUP_BY, FILTER, SORT, WINDOW, CONDITIONAL.
description string Optional. A string representation of the transformation applied.
masking boolean Optional. Boolean value indicating if the input value was obfuscated during the transformation.

Example:

models:
  orders:
    fields:
      order_id:
        type: string
        lineage:
          inputFields:
            - namespace: com.example.service.checkout
              name: checkout_db.orders
              field: order_id
              transformations:
                - type: DIRECT
                  subtype: IDENTITY
                  description: The order ID from the checkout order
            - namespace: com.example.service.checkout
              name: checkout_db.orders
              field: order_timestamp
                - type: INDIRECT
                  subtype: SORT
      customer_email_address_hash:
        type: string
        lineage:
          inputFields:
            - namespace: com.example.service.checkout
              name: checkout_db.orders
              field: email_address
              transformations:
                - type: DIRECT
                  subtype: Transformation
                  description: The email address from the checkout order, hashed with SHA-256
                  masking: true

Config Object

The config field can be used to set additional metadata that may be used by tools, e.g. to define a namespace for code generation, specify physical data types, toggle tests, etc.

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

For developer experience, a list of well-known field names is maintained here, as these fields are used in the Data Contract CLI:

Field Type Description
avroNamespace string (Only on model level) The namespace to use when importing and exporting the data model from / to Apache Avro.
avroType string (Only on field level) Specify the field type to use when exporting the data model to Apache Avro.
avroLogicalType string (Only on field level) Specify the logical field type to use when exporting the data model to Apache Avro.
bigqueryType string (Only on field level) Specify the physical column type that is used in a BigQuery table, e.g., NUMERIC(5, 2)
snowflakeType string (Only on field level) Specify the physical column type that is used in a Snowflake table, e.g, TIMESTAMP_LTZ
redshiftType string (Only on field level) Specify the physical column type that is used in a Redshift table, e.g, SMALLINT
sqlserverType string (Only on field level) Specify the physical column type that is used in a Snowflake table, e.g, DATETIME2
databricksType string (Only on field level) Specify the physical column type that is used in a Databricks table
glueType string (Only on field level) Specify the physical column type that is used in a AWS Glue Data Catalog table

This object MAY be extended with Specification Extensions.

Example:

models:
  orders:
    config:
      avroNamespace: "my.namespace"
    fields:
      my_field_1:
        description: Example for AVRO with Timestamp (millisecond precision)
        type: timestamp
        config:
          avroType: long
          avroLogicalType: timestamp-millis
          snowflakeType: timestamp_tz

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
  • Map: map (may not be supported by some server types)
  • 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 field can be added with any name. The value can be null, a primitive, an array or an object.

Tooling

  • Data Contract CLI is an open-source CLI tool to help you create, develop, and maintain your data contracts.
  • Data Contract Manager is a commercial tool to manage data contracts. It includes a data contract catalog, a Web-Editor, and a request and approval workflow to automate access to data products for a full enterprise data marketplace.
  • Data Contract GPT is a custom GPT that can help you write data contracts.
  • Data Contract Editor is an open-source editor for Data Contracts, including a live html preview.

Code Completion

The JSON Schema of the current data contract specification is registered in Schema Store, which brings code completion and syntax checks for all major IDEs. 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

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

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