Thought leadership
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June 2, 2023

Six key use cases for data contracts

What is a data contract, and who uses it in the real world? This post explores six use cases across several industries where data contracts can help.

Liz Elfman
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Data contracts have become instrumental to ensuring efficient and secure data movement.

Essentially, a data contract is a formal agreement between two parties outlining how data is exchanged, processed, and maintained. The contract is usually between the users of a system and the data teams extracting data from that same system.

The term was originally coined by Andrew Jones of GoCardless. It establishes guidelines about what kind of data is involved, how it will be accessed, used, and protected, and the responsibilities of each party touching the data. Moreover, data contracts provide an essential layer of transparency in an environment where data mismanagement can lead to grave consequences.

What does a data contract look like in the real world? Here are six key use cases where data contracts would play a major role.

1. Data in e-commerce

E-commerce platforms deal with large volumes of data daily: transaction details, customer information, product listings, and vendor information, for example. Using data contracts, these platforms can manage the data exchange across different areas within the platform, like the customer interface, payment gateways, or supply chain systems. Data contracts can also help provide insight into which teams are responsible for data reliability, technical trouble shooting, and marketing campaign analysis.

2. Privacy in healthcare

In the healthcare space, patient data is highly sensitive and requires rigorous safeguards. Data contracts in healthcare, often between hospitals, clinicians, patients, and third-party service providers, can ensure that every piece of data is handled with the utmost care, while respecting patient privacy. Moreover, these contracts define who can access the data, how it can be used, and how long it's retained.

3. Managing IoT devices

The Internet of Things (IoT) is a network of interconnected devices that exchange data. The complexity of this network necessitates data contracts to govern interactions. For instance, a smart home system might involve multiple IoT devices like thermostats, security cameras, and lighting systems, that each produce types of data. A data contract between device manufacturers can regulate how these devices communicate and share data, ensuring interoperability and security.

4. Interoperability in microservices architecture

Microservices architecture breaks an application into smaller, independent components, each with a specific role. These services need to communicate effectively. Across teams that interact with microservices, data contracts can define what data is shared, how it's shared, and when. Ultimately, data contracts can contribute to a framework that enables microservices to work while remaining loosely coupled and maintainable.

5. Enhancing reliability in business analytics

Business analytics rely on high-quality data to generate insights. But data comes from various sources, each with their own structures and standards. Some data is from qualitative feedback, and other data is from quantitative campaign calculations. Data contracts can set clear guidelines on the format, structure, and quality of data that's being contributed and analyzed.

6. Regulating AI and ML models

In AI and machine learning models, the quality and structure of input data significantly influences the results. Data contracts in this context can regulate the flow of data into these models, setting standards for data format, quality, and privacy. Moreover, they can outline the requirements for data handling, storage, and retention for legal and compliance purposes.

Final thoughts

Data contracts are a powerful tool for managing the complex web of data interactions that exist today. They're useful across most industries; after all, what working environment isn't improved with secure, reliable data exchange?

As data continues to grow in value and complexity, data contracts will probably become even more critical to the future of data management.

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Resource
Monthly cost ($)
Number of resources
Time (months)
Total cost ($)
Software/Data engineer
$15,000
3
12
$540,000
Data analyst
$12,000
2
6
$144,000
Business analyst
$10,000
1
3
$30,000
Data/product manager
$20,000
2
6
$240,000
Total cost
$954,000
Role
Goals
Common needs
Data engineers
Overall data flow. Data is fresh and operating at full volume. Jobs are always running, so data outages don't impact downstream systems.
Freshness + volume
Monitoring
Schema change detection
Lineage monitoring
Data scientists
Specific datasets in great detail. Looking for outliers, duplication, and other—sometimes subtle—issues that could affect their analysis or machine learning models.
Freshness monitoringCompleteness monitoringDuplicate detectionOutlier detectionDistribution shift detectionDimensional slicing and dicing
Analytics engineers
Rapidly testing the changes they’re making within the data model. Move fast and not break things—without spending hours writing tons of pipeline tests.
Lineage monitoringETL blue/green testing
Business intelligence analysts
The business impact of data. Understand where they should spend their time digging in, and when they have a red herring caused by a data pipeline problem.
Integration with analytics toolsAnomaly detectionCustom business metricsDimensional slicing and dicing
Other stakeholders
Data reliability. Customers and stakeholders don’t want data issues to bog them down, delay deadlines, or provide inaccurate information.
Integration with analytics toolsReporting and insights

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