# Data & AI on Public Cloud

Wells Fargo · 2023 – 2024 · Role: Served as chief architect for Data & AI on public cloud

> A multi-cloud Data & AI strategy and reusable, pre-approved archetypes that made public-cloud onboarding much faster and modernized a legacy data warehouse.

## Problem

Lines of business were adopting cloud data and AI services one design at a time, with inconsistent controls and duplicated effort.

## Approach

- Defined a multi-cloud Data & AI strategy with strategic, logical and physical reference architecture, a target state and a phased roadmap.
- Enabled managed AI platforms and the model development lifecycle for predictive and generative models on public cloud.
- Created prescriptive, reusable Cloud Data & AI archetypes so teams could start from an approved pattern.

## Governance

- Controlled data movement and enterprise data controls built into every archetype.
- Architecture-led delivery, with every archetype approved once through enterprise architecture review.

## Outcome

- Public-cloud onboarding cut from months to weeks using the archetypes and codified patterns.
- One approved path for a growing set of cloud data and AI services across lines of business.
- A legacy data warehouse modernized to a cloud lakehouse at lower infrastructure cost.

## Lesson

Reusable, pre-approved patterns beat one-off reviews: they make the compliant path the fastest path.

Technologies: Public cloud, Multi-cloud, Managed AI platforms, Cloud data warehouse, Lakehouse, Data pipelines

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Muthukrishnan (Muthu) Bommiah · https://muthub.org · Views are my own and do not represent my employer.