Understanding Data Products and Data Contracts: Building Trust in Modern Data Management

Learn how data products and data contracts transform raw data into reliable assets. Explore the roles of Code & Config, Metadata & Infrastructure, and domain management in ensuring data quality, access control, and trust within your organization

By

Jatin S

Updated on

October 28, 2024

In this AI era, data is the heartbeat of every modern organization. But raw data, much like crude oil, isn't immediately useful. It needs to be refined and transformed into something meaningful. This is where Data Products and Data Contracts come in, helping organizations manage their data better while ensuring that everyone—whether they’re a data engineer or a business leader—can trust the information they’re working with.

Let's break these concepts down in a simple, approachable way, so even a 10th grader could understand the immense value they bring to data teams.

What Exactly Are Data Products?

Think of data products as specially crafted, ready-to-use packages of data designed to solve specific business problems or support particular processes. Whether you're building an AI model or performing an analysis, these "products" are the carefully curated and cleaned-up data sets you rely on to get the job done.

Just as physical products are assembled with care and quality control, data products go through various processes to ensure they are accurate, reliable, and fit for purpose. They aren’t just any collection of data thrown together—they are the result of carefully designed systems that ensure the data is useful.

Diving Deeper into Code & Config

The backbone of any data product is its Code & Config. This is the engine that powers the transformation of raw data into polished, usable products.

Pipeline Code for Consumption, Transformation, and Serving: This is where the raw data gets filtered, cleaned, and reshaped. Think of it as a factory where the raw ingredients (data) are processed into the final product (the curated dataset). Pipelines ensure that data is transformed consistently and reliably, following the same steps every time.
Configuration for Data Quality Checks, Policies, and Thresholds: Data quality is critical. It’s not enough to just have data; you need to be sure that it’s correct, up-to-date, and meets the standards that your business needs. Configuring rules and thresholds helps data teams automatically check for issues like missing values or inconsistent formats, reducing the risk of errors down the line.
Data Governance—Access Control & Logging: Data governance ensures that data is handled responsibly. This means defining who can access what data, tracking who interacts with it, and ensuring that all actions are logged. Access control is especially important when dealing with sensitive or regulated information, and governance policies ensure that data usage complies with legal or company guidelines.
Data Product-Specific Infrastructure & Access Control: Every data product may have unique infrastructure requirements. Some data might need high levels of security or specific storage solutions. This component makes sure the data is served with the correct security and access layers, ensuring that only authorized users can access it.

Expanding on Metadata & Infrastructure

When we talk about Metadata & Infrastructure, we’re talking about the "information about the information." It's like a map that tells us where the data came from, what it means, and how it can be used. Metadata is vital for navigating the complex world of data.

Data Observability: In the same way that a doctor monitors a patient's vital signs, data observability tracks the health of your data pipelines. It helps ensure that data flows smoothly, without unexpected errors, missing records, or other issues that could affect your business.
CI/CD Pipelines: Continuous integration and continuous delivery (CI/CD) pipelines allow teams to deploy changes in their data processes quickly and efficiently. These pipelines automate the testing and rollout of new data products or features, ensuring the system remains reliable even as things evolve.
Catalog—Exposing Technical & Business Metadata, Alerts, and Metrics: A data catalog acts like a well-organized library, making it easy for anyone in the organization to find the data they need. It exposes both technical details (like where data lives and its format) and business definitions (like what the data means for a company’s operations). Alerts and metrics add another layer of visibility, helping teams quickly respond to any issues that crop up.
Outcome Interfaces (APIs, BI Reports, Dashboards): This is how end-users interact with data products. APIs allow other systems or applications to tap into your data. Business intelligence (BI) reports and dashboards, on the other hand, present the data in a visual format, making it easier for humans to interpret and act on.

Sample Config files:


# Data Product Configuration for Sales Data Pipeline
data_product:
  name: SalesDataPipeline
  version: 1.2
  description: "Processes and serves sales data for consumption by the business intelligence team."
  domain: Sales  # Domain management to group data by business function
  access_control:  
    roles:
      - role: sales_analyst
        access: read-only  # Sales analysts have read-only access
      - role: sales_manager
        access: read-write  # Sales managers can read and update records
      - role: data_engineer
        access: admin  # Data engineers have full control over the pipeline

Domain Management and Access Control

An important concept in modern data management is domain management. As organizations grow, they often split their data into different domains—logical groupings of data based on business functions, such as Sales, Marketing, or Finance.

Managing these domains is crucial to maintaining order and security. By organizing data into domains, you ensure that only the right people have access to specific datasets. Each domain might have different rules for how data is processed and accessed, reflecting the unique requirements of each department or team. Access control within domains is critical to ensure that sensitive information is protected, and users only see the data they are authorized to work with.

For example, sales teams should not have unrestricted access to financial data, and vice versa. Domain-based access control allows businesses to apply fine-grained security, ensuring both privacy and compliance with regulations.

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Data Contracts: Bringing Order and Trust to Data Management

Now that we have a clear understanding of what data products are, let’s move on to data contracts.

A data contract is essentially a formal agreement between the data producers (those who generate or prepare the data) and the data consumers (those who use it). It’s a mutual understanding that defines what the data should look like, how often it will be updated, and what quality thresholds it must meet.

Think of it like ordering a meal at a restaurant. You expect certain standards—the food should be fresh, cooked properly, and delivered on time. A data contract works in a similar way, ensuring that data consumers get the "meal" they need without having to worry about whether it will meet their expectations.

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Benefits of Data Contracts for Producers and Consumers

For Data Producers:
- Clarity on Expectations: With a data contract, producers know exactly what the consumers need. This reduces miscommunication and ensures that they deliver the right data, at the right time, in the right format.
- Streamlined Data Pipelines: Knowing exactly what data is required allows producers to optimize their processes, eliminating unnecessary steps and improving efficiency.
For Data Consumers:
- Trust in Data Quality: With contracts in place, consumers can trust that the data they’re using is reliable and meets the agreed-upon standards.
- Reduced Data Errors: Since contracts define quality thresholds and validation steps, consumers experience fewer data-related issues, saving time and resources.

Building Trust in Data Ecosystems

At the heart of all this lies trust. Without trust, data cannot be effective. Data contracts and the careful design of data products help build that trust. When everyone in the data ecosystem—from engineers to analysts—knows what to expect, data flows more smoothly, leading to faster decisions and greater innovation.

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Wrapping Up

In the modern world, data is more than just numbers and facts. It’s a critical asset that fuels decision-making, innovation, and business success. By turning data into products and establishing clear contracts between those who produce and consume it, organizations can unlock the full potential of their data, ensuring reliability, accuracy, and trust at every step.

And this is where Decube excels. We take care of the complex details—like observability, data contracts, and domain management—so your teams can focus on what truly matters: leveraging data to drive success.

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