If data governance establishes an organization’s “data rules of the road,” then an effective data architecture practice is a key capability for enforcing aligned principles, policies, guidelines and standards. Many organizations have similarities in the way data architecture and data governance operate: both have a framework, an enterprise perspective that data supports the organization, and both seek to establish processes that are sustainable and forward-looking. Our well defined approach combines and leverages data architecture and data governance capabilities to find synergies and success in overcoming common obstacles.
A robust data architecture also provides an understanding of where data exists and how it travels throughout an organization and its systems — highlighting changes and transformations made as data moves from one system to the next, on prem or in the cloud. Large organizations have traditionally housed information in multiple applications, business systems and other databases. Forward-thinking companies have long seen integrating these systems as business-critical, but inconsistencies in data types and structures often hamper these efforts.
That’s where we come in.
Our highly skilled data architecture team has decades of experience helping organizations implement effective, sustainable data architecture and integration programs, with collaborative governance in alignment. By fostering synergy between the governance and architecture groups — and their people, processes and policies — your data management function will reap the rewards of a stronger structure and one that supports key business objectives (and improved outcomes).
FSFP’s data architecture consultants can help you:
- Complete a visioning exercise to understand your desired data architecture future state and identify what in your current data, data structures and data management capabilities are limiting achievement of that future state
- Stand up a sustainable data architecture practice that works closely with other architecture functions as well as data governance to ensure data is reliable, available, trusted and actionable
- Ensure your data structures and data models reflect your most critical use cases and business needs
- Rationalize and optimize key enterprise-wide data source systems and integration points, balancing your requirements against modern best practices and value-add technologies
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