Data Architecture

Data architecture is foundational to any technology application. It consists of the rules and policies for gathering, storing, and integrating data for use in your systems. Good data architecture will meet the requirements of a system project while fitting into an enterprise’s larger strategy.

Critical Foundation

People ask why good data architecture is important and who can benefit from it. Many systems begin as a quick solution to an initial problem and then grow over time. These systems will often experience significant issues as they outgrow their initial data model. Adding new features and changing business requirements contribute to accumulating technical debt. Ideally, we consider data architecture before beginning any system development effort. In practice, most people are reluctant to change a system that is already in place. Don’t be afraid to rearchitect your existing data structure so you can pay down your technical debt.

Broad Vision

Data architecture requires a broad, holistic approach. Just as a carpenter needs more than a hammer, not every data requirement fits into a relational database. A good data architect will use the full breadth of technology available and understands more than data structures, storage limitations, and database technologies. A good architect has a vision and works with a project team to probe for current and future requirements.


DSS uses a technique called User Story Mapping to discern a customer’s process and the data needed to complete the process. We flesh out both transactional and analytical requirements that feed into a conceptual data model. DSS’s experience building and supporting various applications over the decades is the source of our expertise. Whether it is a financial information system or applications in product supply chains, we understand the criticality of data architecture and how best to engineer the right solution.


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Good data architecture is the base upon which you will build your system.

  • Start with a sound foundation
  • Plan for the future
  • Be holistic


Focus on the broader data requirements from design through implementation.

  • Be agile
  • Maintain the vision
  • Avoid technical debt


Business requirements constantly change.  Your data architecture needs to keep up.

  • Challenge assumptions
  • Evaluate alternatives
  • Embrace new technologies

Why Choose DSS

Thirty years of Experience

Longevity comes from keeping customers satisfied, and we've been providing satisfaction for a few decades.

  • Multi-discipline approach
  • Superior technology
  • Business understanding
  • Enabling self-service
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