Legacy systems, architecture constraints, rising costs and security or performance issues can make it difficult to determine where data modernisation should begin. A clear understanding of the current environment helps organisations prioritise investment, reduce uncertainty and make informed platform decisions.
A data platform assessment evaluates the architecture, performance, scalability, security, governance and cost of an organisation’s existing data environment. It identifies constraints and opportunities, assesses readiness for modern analytics and AI, and defines a practical target-state architecture and modernisation roadmap.
Arinco’s Data Assessment is a focused 2–6 week engagement combining targeted workshops with technical analysis. Recommendations are shaped around your business priorities, existing technology and future data requirements.
Gain a clear view of your current data environment and key constraints.
Identify gaps and opportunities across architecture, cost, security, performance and scalability.
Prioritise the next steps for data platform modernisation.
Centralise security, API management and observability with Azure-native services.
A data platform assessment is a structured review of an organisation’s existing data environment. It examines areas such as architecture, security, governance, cost, performance and scalability to identify risks, improvement opportunities and the most appropriate path to modernisation.
An assessment can help when legacy systems are limiting performance, cloud costs are increasing, data is difficult to access or govern, or the organisation is preparing for migration, modern analytics or AI. It can also provide clarity before committing to a major platform investment.
AI depends on accessible, trusted and appropriately governed data. A data platform assessment can identify gaps in architecture, data quality, security, governance and scalability that should be addressed before AI workloads are introduced or expanded.
Talk to Arinco about assessing your current data environment, defining a target-state architecture and creating a practical roadmap for data modernisation and AI readiness.
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