Data architecture is arguably the single most important discipline of modern data management.

We live and work in a data-centric world. Nearly everything that we see and do is described by data – every asset, resource, event, interaction, transaction, and outcome. All of this data is combined, processed, and analyzed for purposes that range from simple record-keeping to analytics, artificial intelligence, and generation of new data and information. The abundance of data, together with AI/ML capabilities, creates rich opportunities for value creation but also presents real and tangible risks. Data architecture that is focused on business capabilities and driven by business requirements is essential to creating value from data reliably and mitigating the inherent risks of data.

Think of architecture as the conceptual framework that ties everything together beginning with data strategy and progressing through many layers of use cases, processes, practices, applications, and technologies, and ultimately extending to databases and physical storage of data. Robust and well-rounded data architecture provides structure, standards, and guidelines for data lifecycles, usage, protection, content, structure, processing, storage, and technologies. Sustainable data architecture continuously adapts to changes in the realities of business, data, and technology. To survive in today’s dynamic and fast-paced world you need to have good data architecture. To thrive, you’ll need exceptional data architecture.