---
title: "Azure Data Foundation PoC | Data-Driven AI"
canonical: "https://data-driven.com/data-foundation-solution-3/"
description: "Review Data-Driven AI's four-week Azure Data Foundation proof of concept, from a defined use case through ingestion, transformation, and Power BI insight."
---

Microsoft Marketplace consulting service

# Build an Azure data foundation around _one defined use case_

Use a four-week proof of concept to test the platform path from ingestion and transformation to an insight stakeholders can review.

Offer boundary

## The four weeks are organised around a use case

The current Microsoft Marketplace listing describes a four-week engagement that delivers a modern data platform on Azure. It covers an end-to-end path through ingestion, transformation, a serving layer, and a Power BI insight for the agreed use case.

[Open Microsoft Marketplace](https://marketplace.microsoft.com/en-us/product/saas/data-drivenai1581501556049.dfp-ip-co-sell-saas?tab=overview)[Discuss a data foundation scope](/contact-us/)

![Azure Data Foundation proof-of-concept artwork](/_astro/Data-Foundation-Solution-768x694.mlJ4aveo_Z1br1em.webp)

Offer artwork retained from the original Data Foundation page.

Platform mechanism

## Follow the data from source to a reviewable result

The retained architecture shows the intended pipeline shape. The final services and boundaries depend on the source systems, access model, and chosen use case.

![High-level Azure Data Foundation architecture from source systems through processing and analytics](/_astro/Data-Foundation-Architecture-noopt-1024x351.XVoASlp8_1h7QSn.webp)

High-level architecture retained from the original offer page.

Delivery path

## The proof of concept moves through three decisions

The sequence follows the published Marketplace offer. It does not assume that every source or future use case is included.

Choose

Select the first business use case and the people who own it.

Build

Implement the agreed Azure data-platform path.

Review

Surface the Power BI insight and decide what should happen next.

Architecture review

## Use the Azure Well-Architected pillars as questions, not decoration

The Microsoft Azure Well-Architected Framework covers reliability, security, cost optimisation, operational excellence, and performance efficiency. Each pillar should shape the design review for the selected workload.

### Reliability

Define the failures, recovery needs, and service expectations that matter for this workload.

### Security

Set identity, access, data, network, and monitoring boundaries before delivery.

### Cost optimisation

Relate cost choices to workload value and the operating model that will own them.

### Operational excellence

Plan deployment, monitoring, ownership, and change practices for the platform.

### Performance efficiency

Match resource choices to demand and measure whether the design meets its target.

[Review the five pillars in Microsoft Learn](https://learn.microsoft.com/en-us/azure/well-architected/pillars).

Scope the four weeks

## The timeline only works when the inputs are ready

Confirm source access, representative data, stakeholder time, and the definition of the final insight before treating the four-week duration as a delivery plan.

![Four-week Data Foundation proof-of-concept timeline](/_astro/Data-Foundation-TImeline-noopt-1024x380.DjCLbwdY_ZxlaI8.webp)

Timeline retained from the original offer page; final milestones depend on the agreed scope.

## Have a use case for a data foundation?

Bring the data sources, users, decision, and evidence the proof of concept must produce.

[Review the Marketplace offer](https://marketplace.microsoft.com/en-us/product/saas/data-drivenai1581501556049.dfp-ip-co-sell-saas?tab=overview)

[Explore Fabric analytics](/services/fabric-advanced-analytics/)

## Want to learn more?

Explore the rest of the site or get in touch with the team.

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