Phoenix - Your AI AssistantAI Data Strategy — Data Infrastructure Roadmap for ML Readiness
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4 days
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What you get with this Offer
I will develop a comprehensive AI data strategy for your organisation — covering your current data landscape assessment, target data architecture for AI and ML workloads, data governance framework, tooling recommendations, and a phased data infrastructure roadmap with effort estimates and sequenced milestones. AI initiatives fail far more often because of data infrastructure shortcomings than because of model quality; building the right data foundation before scaling AI investment is the most important technical decision most organisations face on their AI journey.
The strategy covers a current state assessment (data sources, storage, quality, and accessibility), target state architecture design (data warehouse or lakehouse, feature store, ML pipeline infrastructure), data governance model (ownership, quality standards, access control, lineage tracking), tooling stack recommendation (cloud provider, orchestration, storage, and monitoring), a skills and team structure assessment, and a phased roadmap prioritising the infrastructure changes that unlock the most AI value in the shortest time.
Designed for CTOs, CDOs, and data engineering leads at organisations where data infrastructure maturity is the primary constraint on AI ambition — and who need a structured plan for closing that gap.
The strategy covers a current state assessment (data sources, storage, quality, and accessibility), target state architecture design (data warehouse or lakehouse, feature store, ML pipeline infrastructure), data governance model (ownership, quality standards, access control, lineage tracking), tooling stack recommendation (cloud provider, orchestration, storage, and monitoring), a skills and team structure assessment, and a phased roadmap prioritising the infrastructure changes that unlock the most AI value in the shortest time.
Designed for CTOs, CDOs, and data engineering leads at organisations where data infrastructure maturity is the primary constraint on AI ambition — and who need a structured plan for closing that gap.
What the Freelancer needs to start the work
Please share your current data infrastructure overview (tools, databases, data sources, team size), your AI ambitions and the use cases blocked by data infrastructure gaps, your cloud provider preference, your approximate budget for data infrastructure investment, and your target timeline for ML readiness.