Gable Blog | What Are Data Contracts?

Get the ultimate guide to Data Contracts Deep Dive

Get the ultimate guide to Data Contracts as Code

Discover where your data really comes from.

Ultimate Guide to Data Contracts

What is a data contract?

A data contract is a formal agreement between two or more parties that outlines specific terms and conditions of data sharing. These contracts can exist between organizations, systems, or individuals.

Where traditional contracts exist as written or spoken agreements, data contracts tend to encompass a combination of documents, tools, and artifacts that provide clear specifications, assurances, and systems to monitor and manage the data exchange between parties.

How do data contacts work?

In practice, the formal agreement that data contracts represent will marshal the exchange, handling, storage, and usage of data. Contracting parties agree to ensure that any data outlined in the contract is managed accurately and securely, remaining in compliance with relevant regulations.

These agreements aren’t hypothetical. A contract only works if it can be enforced. This is why data contracts that involve software should be programmatic.

Operationally, contracts will commonly include the following:

• Schema definitions: A data contract should explicitly define the schema, including semantics, so the structure of data is clear.
• Validation rules: These rules make sure all ensuing data adheres to the defined schema and will meet data quality standards the contracting parties require.
• Access control: Data contracts may specify who approved data producers and data consumers will be for the duration of time specified within the contract.
• Data flow management: Contracts typically outline how datasets should flow between specific systems like data pipelines and data ingestion processes.
• Communication protocols: API specifications and communication protocols may also be outlined to standardize the data exchange between systems and platforms.
• Versioning: Data contracts implement versioning to manage changes made to the data schema.
• Dependency and metadata management: To make sure changes don’t negatively impact dependent systems, dependencies between different data entities may also be managed as part of a data contract.
• Compliance and auditing: Data contracts will ensure that all data exchange and management adhere to legal and compliance requirements.
• Error handling: Finally, as much as data contracts work to make sure things go right, they should also guide responses when things go wrong.

Essential aspects of the contract drafting process

Having defined what a data contract is and what it should typically entail, we can turn to how they’re implemented.

1. Objectives and parameters

Effective data contracts begin with defining the landscape in which they’ll operate. Relevant stakeholders and use cases to which the contract will pertain should be included.

2. Schema design and management

Next, a clear and comprehensive scheme should be defined using formats like YAML, JSON, or Avro to detail data structure, formats, and types.

3. Data quality assurance

Validation rules can then be established to ensure optimal data quality and consistency.

4. Technical implementation

Different enforcements of the contract, such as those involving SQL queries, will be needed depending on the technologies used.

5. SLA, security, and compliance

Specifics regarding data quality, latency, and availability will be clearly defined and minted in the data contract’s SLA.

6. Communication, error handling, and resolution

Data contracts should facilitate collaboration between data engineers, other data teams, and data consumers.

7. Documentation and changes

Robust documentation and change management must also be captured during the drafting process.

8. Continuous improvement

As a data contract actively guides the use of data, feedback loops need to be established with data consumers and producers.

9. Technology, tooling, and testing

With the previous aspects defined, appropriate tools and technologies can be chosen to implement the contract.

Three use cases for data contracts

Real-time data streaming in financial services

• Accuracy: Ensure data is both available and guaranteed to adhere to expected formats.
• SLA management: Ensure that data latency remains within acceptable parameters.
• Security: Ensure sensitive financial data remains secure during transmission.

Collaborative data ecosystems in healthcare

• Data quality: Ensure accurate and reliable data among entities.
• Data privacy and compliance: Define how sensitive health data can be handled.
• Interoperability and dependency management: Ensure consistency and interoperability necessary in healthcare ecosystems.

Supply chain management in retail

• Data integration: Facilitate data integration across relevant entities.
• Transparency and traceability: Ensure the journey products take is traceable and transparent.
• Automation: Govern a seamless flow of data across the entire supply chain.