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Create a Data Contract

Data contracts define expectations for a data asset across schema, quality, security, and service levels.

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Step 1: Open the Contract Tab

1. On the Explore Assets page, open an asset.
2. Select the Contract tab and click Add Contract.

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Step 2: Contract Details

An Add Contract Details wizard opens with seven sections in the left sidebar: Contract Details, Terms of Service, Schema, Semantics, Security, Quality, and SLA.

1. Fill in the contract’s basic information:
   • Contract Title (required) — Enter a name for the contract.
   • Owners — Select one or more owners from the directory.
   • Description — Add a description using the rich text editor.
2. Click Terms of Service to continue.

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Step 3: Terms of Service

1. Enter the rules and conditions that consumers of this data asset agree to. Use the rich text editor — type / to access formatting commands.
2. Click Schema to continue.

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Step 4: Schema

The Schema section lists all columns from the asset, pre-populated with their type, tags, glossary terms, and constraints.

1. Select the columns to include in this contract, or check the top box to select all.
2. Click Semantics to continue.

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Step 5: Semantics

Semantics define business documentation rules the asset must meet. Click Add Semantics to create a rule. See Understanding Semantic Rules for a full list of supported fields and how to combine conditions.

1. Enter a Name (required).
2. Enter a Description (required).
3. Configure the Rule using the query builder — select a field, operator, and value. Supported fields include:
   • Service, Owners, Display Name, Name, Description, Tags, Domain, Data Product, Tier
4. Click Add New Rule within the query builder to add more conditions to the same rule, or click Add Semantics to create an additional rule.
5. Click Security to continue.

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Step 6: Security

Security expectations cover classification, access policies, and row-level filters. See Security Settings Explained for guidance on when and how to use each field.

1. Fill in the following details:
   • Data Classification — Enter the classification label for this asset (for example, PII, Confidential).
   • Policies — Click + Add Policy to define an access policy:
     • Access Policy — Name of the access policy.
     • Identities — Users or groups the policy applies to.
   • Row Filters — Click + Add Row Filter to restrict visible rows by column value:
     • Column Name — Select the column to filter on.
     • Values — Enter the allowed values for that column.
   
2. Click Quality to continue.

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Step 7: Quality

The Quality section lists existing data quality tests for the asset and their current status.

1. Select tests to include in the contract, or click + Add Test to create a new test case. See Create Quality Test Case.
2. Click SLA to continue.

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Step 8: SLA

SLA defines the service level expectations for this asset. See SLA Fields Explained to understand the difference between each time-related field.

1. Fill in the following fields:
   • Refresh Frequency — Set the expected update interval and unit (hour, day, week, month, or year).
   • Max Latency — Set the maximum acceptable delay between data generation and availability, in minutes, hours, or days.
   • Availability Time — Set the time of day by which data must be available, and select a timezone.
   • Retention — Set the data retention period and unit (day, week, month, or year).
   • Column > Column Name — Select the column that represents the refresh timestamp of the data.
   
2. Click Save to create a contract.

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Understanding Semantic Rules

The rule builder uses a three-part structure: field | operator | value. Each combination creates one condition that the asset must satisfy.

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Supported Fields

The following fields are available in the rule builder:

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Combining Conditions

• Click + Add New Rule within a semantic card to add another condition to the same rule.
• Click + Add Semantics to create a separate, independent rule.

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Example

To enforce that every asset in a contract has an owner assigned and is tagged:

1. Click + Add Semantics. Enter Name Ownership Required, then set the Rule to Owners | Is | <owner-or-team>. Click Save.
2. Click + Add Semantics again. Enter Name Tag Required, then set the Rule to Tags | Is | <tag-name>. Click Save.

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Security Settings Explained

The Security section has three components, each serving a different purpose.

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Data Classification

Data Classification is a free-text label that identifies the sensitivity level of the asset. Common values include PII, Confidential, Internal, and Public. This label is informational — it does not automatically enforce access controls, but makes the classification visible to contract consumers.

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Policies

A policy defines who the intended consumers of this data are. Each policy has two fields:

• Access Policy — A name identifying the policy (for example, analytics-read-only).
• Identities — The users, teams, or groups the policy applies to.

Add multiple policies when different groups have different levels of access to the same asset.

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Row Filters

Row Filters restrict which rows a consumer can see when querying this asset. Each filter targets one column:

• Column Name — The column to filter on (for example, country).
• Values — The allowed values for that column (for example, US).

Example: A contract on a global orders table with a row filter country = US ensures that consumers governed by this contract only see rows where country is US.

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SLA Fields Explained

The SLA section captures four distinct time-related expectations. Understanding the difference between them helps you set accurate commitments.

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Refresh Frequency vs Max Latency

These two fields are often confused:

• Refresh Frequency is about cadence — the asset is expected to update once a day, once a week, etc.
• Max Latency is about delay tolerance — after the upstream source produces data, how long before it must appear in this asset.

A pipeline that runs daily but must reflect changes within 2 hours of upstream production would have a Refresh Frequency of 1 day and a Max Latency of 2 hours.

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Column

Select the column that holds the timestamp of each row’s last refresh. Collate uses this column to verify data freshness against the Refresh Frequency expectation.