Microsoft Practice

The full Microsoft
data platform.
Production-ready.

DataQubi's financial hardening engagement runs on Microsoft Fabric. The same team builds the broader data foundations: Lakehouse architecture, Power BI semantic models, Copilot Wave 3 deployments, and the Azure infrastructure beneath all of it. Deep stack, one firm. Current on every 2026 release.

28K+orgs now on Fabric globally
90%Fortune 500 using Copilot
160%Copilot seat growth YoY
7Microsoft practice areas
Discuss Your Project About the team

Seven practice areas

Everything your Microsoft
data platform needs

From storage architecture to AI applications. Each capability delivered as a focused engagement with honest timelines.

Microsoft Fabric
OneLake as your EBITDA intelligence layer, unifying finance, operations, and procurement data across your Azure tenant.
10-week implementation
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Power BI
Semantic models that encode business logic. Executive dashboards. Self-service analytics with governance guardrails. Reports people actually trust.
8-week implementation
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Microsoft Copilot
Wave 3 is live. M365 Copilot + Agent 365 + Cowork deployment, readiness assessment, and custom Copilot Studio agents. AI that actually gets used, built for your workflows, grounded in your data.
10-week rollout
Full details at copilot.dataqubi.com
Azure AI Foundry
RAG applications grounded in your data. AI agents that automate real business processes. From prototype to production, without rebuilding the architecture.
14-week implementation
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Microsoft Purview
Data catalog, lineage tracking, sensitivity classification, and access policies. Governance that gets used, configured during implementation, not six months later.
10-week implementation
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Azure Infrastructure
ADLS Gen2 architecture, private endpoints, managed identities, RBAC design, and security baseline. The foundation beneath your data platform, configured for sensitive workloads.
6–8 week engagement
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Azure DevOps
Version control for data assets, CI/CD pipelines, data quality testing gates, Fabric Git integration, and Power BI deployment pipelines. Engineering discipline for analytics teams.
6-week engagement
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Why Microsoft

One stack.
No integration tax.

For organizations already in the Microsoft ecosystem, the stack integrates in ways Databricks and Snowflake can't; it doesn't require a separate infrastructure team to maintain.

Native M365 integration
Fabric, Power BI, Copilot, Purview, and Azure share identity, governance, and networking. Build once, apply everywhere, no stitching required.
Data stays in your tenant
Every workload runs inside your Azure environment. Private endpoints, managed VNets, customer-managed keys. No data leaves your control boundary.
SaaS infrastructure
Fabric is SaaS. Less infrastructure to manage than Databricks or Snowflake; your data team focuses on data, not cluster maintenance.

How we work

Focused engagements,
honest timelines

No six-month retainers with ambiguous scope. Each engagement has a defined outcome, a realistic timeline, and a handoff designed for self-sufficiency.

01
Assess before we build
Every engagement starts with a discovery phase. We document what exists, identify gaps, and design the target architecture before writing a line of pipeline code.
02
Deploy in your tenant
All work happens inside your Azure environment. You own every artifact from day one, with no proprietary tooling and no ongoing dependency on our infrastructure.
03
Validate at each stage
Deliverables are tested in dev before they reach production. Data quality gates, schema checks, business rule validation; problems caught before the CFO's dashboard shows them.
04
Build for self-sufficiency
We document the architecture, train your team, and establish processes. The goal is a foundation your people can operate and extend, not an ongoing engagement.

Start with the right
capability for your situation

20 minutes. We'll look at where you are, identify the highest-leverage starting point, and map out a realistic timeline.

Schedule a Strategy Call About the team