Data Architecture Checklist

Use our checklist to ensure best data architecture practices for your research institution or project.

Data architecture defines the data strategy and data flows in organisations. It describes how data is managed from collection to transformation, distribution and consumption. It sets the blueprint for the way data flows through the systems. It also outlines data flows including data collection, transformation, processing and analytics, and decision-making using data science.

To ensure best practices for research projects and institutions, we’ve compiled a checklist consisting of questions covering 17 areas of data architecture. After completing the checklist, you’ll better understand where you stand regarding data architecture and what areas you need to follow up on.

  • Australian Research Data Commons. (2023). Data architecture checklist.

    DOI: 10.5281/zenodo.10051921

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