Optimising Data Architectures and Workflows
Consider these recommendations on keeping your organisation’s data architecture up to best practice.
An organisation’s data architecture needs to keep pace with technological changes. It needs to be responsive not only to ensure the organisation continues to operate efficiently but also to support the overall strategic direction of the organisation.
Here are some recommendations for optimising your data architecture:
- Assess the current state of the architecture. Understand the different parts of the architecture and identify the needs. Translate the objectives into architecture requirements, solutions and changes.
- Identify and prioritise drivers for data architecture improvements and then draw up associated data strategies and workflows.
- Perform a gap analysis between the current state and the future state.
- Create a roadmap or workflow that includes the processes required to transition the existing architecture to its target state.
- Discover best practices trends, assess the present situation and set goals for data architecture techniques.
- Create a unified strategy for reorganising your data infrastructure. Manage your decisions and the changes that arise from them.
- Document your data architecture, including its components, data flows and dependencies. Foster a data-driven culture and promote collaboration between data architects, data engineers, data scientists (AI/ML) and business stakeholders to ensure a shared understanding of the architecture.
- Recruit data architecture experts to advise on projects as they transition from outdated systems and siloed data to integrated data platforms.
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