In today’s rapidly evolving, data-driven world, organisations face an increasingly complex challenge: how to design, implement, and manage data interfaces that meet both immediate operational demands and long-term strategic business objectives. A data interface is a defined connection point where data is exchanged between systems, applications, or components. It specifies the rules, formats, and protocols needed for smooth communication and interoperability, acting as the backbone of modern data ecosystems.
Organisations became aware of data being central to decision-making, driving innovation, and leading to competitive advantage. However, clarity in navigating the myriad possibilities of data interface design is often elusive, particularly for software architects who must bridge the divide between technical solutions and business outcomes.
This is where the Data Interface Quadrants (DIQs) framework steps in as a transformative tool. The DIQs provide a structured, visual approach to understanding and categorising data interfaces, empowering architects, development teams, and decision-makers to navigate complexity with confidence. By distilling the complexities of data interfaces into an intuitive format, DIQs offer insights that drive better strategic alignment and informed decision-making.
In this blog post, we unpack the potential of the DIQs and explore their value through two key lenses: the enterprise architect, who focuses on long-term organisational strategy, and the solution architect, who addresses project-specific implementation challenges. Together, these perspectives reveal how DIQs enable them to collaborate effectively to create and modernise robust, future-proof data ecosystems. The DIQs are more than just a diagram - they are a compass for navigating the trade-offs inherent in data interface design.
Introducing the DIQs
The DIQs offer a structured way to categorise data interfaces along two primary dimensions: the extent of data processing and the scope of its consumers. The horizontal axis of the DIQs focuses on the degree of data aggregation or transformation. On the left side, it emphasises raw data, where minimal or no transformation is applied, catering to use cases that require base-level data in its original form. On the right side, the framework highlights aggregated or transformed data, which is designed to support specific use cases or provide enhanced service-level functionality.
The complexity of data processing increases as you move from raw data to aggregated or transformed data. Raw data requires minimal intervention and is typically faster to provide but may demand more effort from consumers to extract meaningful insights. On the other hand, aggregated or transformed data involves additional processing steps, such as combining datasets, applying business logic, or reformatting data to fit specific use cases. While this adds a layer of complexity to the creation and maintenance of the interface, it can significantly reduce the effort required by consumers, making the data more immediately usable for their needs.
The vertical axis in the DIQs addresses the scope of consumers who interact with the data. At the bottom, the focus is on product-internal or usecase specific interfaces. These are typically consumed by a single team or a well-defined, technical audience with shared expertise. Conversely, the top of the DIQs shifts attention to external and reusable interfaces, which are designed to accommodate multiple teams and diverse audiences. These can include individuals with varying technical skills or even unknown consumers.
The framework defines four quadrants, each representing a specific type of data interface. The Data Link quadrant, located at the bottom-left, represents raw data interfaces used within a single product or team. These interfaces are simple and direct, often involving minimal transformation and primarily serving technical audiences with clear, shared requirements. The Backend for Fronted (BFF) quadrant, positioned at the bottom-right, includes usecase specific interfaces that offer aggregated or transformed data. These interfaces are tailored for particular application needs and are optimised for efficiency within a single product or team context. Development teams usually design and implement both types of interfaces with a strong focus on the technology.
At the top-left, the Platform Data Product quadrant represents raw data interfaces that are external and reusable. These interfaces provide foundational data in its original form to a broad audience, including unknown consumers or those with varying technical backgrounds. They prioritise reusability and scalability over specificity. Finally, the Composition Service quadrant at the top-right captures external and reusable interfaces offering aggregated and transformed data. These interfaces are designed to meet diverse use cases and are consumed by multiple teams, making them the most complex to build and maintain but the most versatile in addressing organisational needs. The broader audience requires development teams to design and implement both types of interfaces with a strong focus on the business requirements instead of technology.
The Implications of an API-First Business Model
As organisations strive to become API-First, APIs become the relevant business model for them. Therefore, the focus for data interfaces shifts more towards the top quadrants of the DIQs. Instead of building product internal and usecase specific interfaces, development teams have to focus on building more external and reusable interfaces for larger audiences which also results in a higher business impact. However, if the team’s experience so far lies in technology building Backend for Frontend interfaces, they might not be aware of what’s needed to build a successful Composition Service aiming for business impact. Enabling and platform teams can empower development teams supporting the shift from APIs as solely technical interfaces to business relevant products. The DIQs can help visualise such strategic decisions and their implications on data interface design.
Enterprise Architects: The DIQs as Strategic Lens
Enterprise architects operate at the intersection of business strategy and technological implementation, thereby also shaping the overarching data architecture. The DIQs equip them with a holistic perspective, enabling strategic oversight that bridges the gap between organisational objectives and technical realities.
Using the DIQs, enterprise architects can categorise and evaluate interfaces, prioritising investments where they matter most. For instance, interfaces that are product internal and usecase specific, offering aggregated or transformed data, can enhance scalability, while those designed for external and reusable purposes, providing raw data, present opportunities for optimisation as they require minimal data processing but have a high impact on the business due to a broad audience. The DIQs also help identify bottlenecks and redundant systems, guiding efforts to streamline processes and enhance integration.
Moreover, the DIQs serve as a communication tool by presenting data interfaces in a clear, visual format. Enterprise architects can use it to facilitate discussions with stakeholders to align technical initiatives with broader business goals. For example, in a digital transformation project, the DIQs help to spotlight interfaces that require redesign or investment, ensuring decisions made today support future growth. In addition, enterprise architects can identify development teams needing more support from enabling and platform teams to make sure that redesign and investment are successful.
Solution Architects: Bridging Strategy and Execution
Solution architects bring ideas to life by designing systems that meet immediate project demands while adhering to broader architectural principles. The DIQs help them navigate competing priorities, offering a structured lens to evaluate and implement data interfaces effectively.
When integrating systems, for example a CRM platform, solution architects face the challenge of balancing rapid delivery with long-term scalability. On one hand, there is pressure to deliver functional solutions quickly to meet immediate business needs, such as enabling a sales team to access critical customer data in real time. On the other hand, these interfaces must also be designed with future growth and integration in mind, ensuring they support evolving requirements, additional systems, and increased data volumes over time. This balancing act is further complicated by competing priorities. Rapid delivery often favors lightweight and minimally complex interfaces that can be implemented quickly with limited resources. However, these interfaces may lack the robustness or flexibility required to integrate seamlessly with future systems or handle growing organisational demands. Conversely, designing for long-term scalability might require additional time and effort upfront, such as implementing aggregated or reusable data interfaces, which can delay initial delivery but significantly enhance the system’s overall resilience and adaptability.
By mapping options within the DIQs, solution architects gain a structured way to evaluate and align their decisions with both immediate project goals and overarching enterprise strategies. For example, lightweight interfaces may expedite delivery, meeting urgent deadlines, but must also be assessed for compatibility with future integrations to avoid costly redesigns. Using the DIQs, they can identify where compromises are necessary and where investments in scalability will pay off, ensuring that short-term achievements do not undermine long-term success.
Collaboration Through DIQs: Bridging Roles
The DIQs transcend individual roles, fostering collaboration between enterprise and solution architects. The quadrants serve as a ubiquitous language, bridging these perspectives to create a cohesive data strategy.
Workshops or planning sessions anchored in the DIQs can align priorities, ensuring tactical decisions contribute to long-term goals. This iterative collaboration not only enhances interface design but also builds trust and synergies between teams. In addition, the DIQs can be a useful tool to communicate interface requirements to development teams and make sure everyone involved has the same understanding of the expected outcome. Especially, if concrete guidelines and best practices for each quadrant are provided.
Conclusion
The Data Interface Quadrants framework (DIQs) is more than a tool - it can serve as a strategic enabler. By mapping critical dimensions of data interfaces into a visual structure, DIQs empower architects and organisations to align technical decisions with business objectives and prioritise investments that drive value. Enterprise architects gain an additional strategic lens for long-term planning, while solution architects use DIQs to ensure project success aligns with broader goals and development teams understand what’s expected from them.
Above all, we created the DIQs to foster collaboration, bridging the gap between strategy and execution. They provide a shared framework that enables architects to navigate complexity, drive innovation, and build resilient data ecosystems. As organisations face the challenges of integration, scalability, and governance, DIQs emerge as an essential resource for clarity, direction, and communication.
Explore the DIQs in your organisation, in your team, or in your project. Use them to analyse, optimise, and elevate your data strategies. Share your thoughts and experiences to help improve them and make the DIQs even more useful in our fast-changing, data-driven world. We’re excited to hear your stories!
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Blog authors
Daniel Kocot
Senior Solution Architect / Head of API Consulting
Do you still have questions? Just send me a message.
Miriam Greis
Lead API Consultant
Do you still have questions? Just send me a message.
Do you still have questions? Just send me a message.