Microsoft Microsoft Practice

Your P&L may be accurate.
Your visibility probably is not.

DataQubi hardens financial data on Microsoft Fabric and Azure, with Databricks where scale demands. We build lakehouse foundations, Power BI semantic models, Copilot-enabled workflows, and secure Azure infrastructure so finance and operations run from one trusted operating view.

It is day three of month-end. Finance has one margin number, operations has another, and the board deck still says "pending validation". By lender review week, your team is reconciling spreadsheets instead of running the business. That is not a reporting issue. It is a financial visibility risk.

1single financial truth across teams
Fasterclose cycles and board prep
Lowercovenant and lender reporting risk
Weeksto value, not multi-year programs
Book Financial Visibility Diagnostic About the team

What's actually broken

The cost is not just bad data.
It is delayed decisions and hidden risk.

Most finance teams do not have a "dashboard problem." They have a reconciliation, trust, and control problem that shows up at month-end, board prep, and lender review.

Close cycles are too slow
Every extra day to close delays pricing, hiring, and cash decisions. Leadership reacts late because the numbers arrive late.
Finance and operations disagree on core metrics
When margin, revenue, or inventory logic differs by team, meetings become arguments about numbers instead of decisions about outcomes.
Spreadsheet sprawl runs critical reporting
Manual exports and offline adjustments create key-person dependency, audit exposure, and fragile reporting right when scrutiny is highest.
Board and lender prep is a fire drill
If reporting confidence is low, your narrative weakens. Covenant discussions become harder because the underlying data cannot be defended quickly.
Access controls are inconsistent
Data is either too open or too locked down, forcing teams into side files outside governance and creating avoidable compliance risk.
AI tools underperform
Copilot cannot deliver executive-grade answers when source data is fragmented, stale, or defined differently across systems.

What we build on Microsoft Fabric

From everyday workloads
to advanced AI

Think of your data ecosystem like a modern logistics fleet. Microsoft Fabric is the commuter car for fast, reliable daily analytics. Azure Databricks is the heavy-duty truck for large and complex data engineering. Purview acts like traffic control so sensitive data is governed but still usable, and Copilot workflows sit on top of trusted models so teams can move faster without guessing.

Right tool, right workload
Most companies need both speed for business users and depth for advanced data teams.

We create a single financial truth across finance and operations, reduce close and report prep effort, and give executives trusted self-serve views into revenue, margin, cash, and operational KPIs.

Typical pattern: Fabric for board reporting, close acceleration, and low-code analytics. Databricks for high-volume ingestion, complex transformations, and advanced analytics where scale requires it.

Commuter Car
Microsoft Fabric
Microsoft Fabric

Fast, reliable, and easy to drive without an expert mechanic. Built for business users who want to connect data, build reports, and automate insight with a low-code and no-code experience.

Best for everyday business workloads
  • Financial dashboards and executive reporting
  • Operational scorecards and sales performance tracking
  • OneLake, Power BI, Data Factory, and governance in one SaaS experience
Heavy-Duty Truck
Azure Databricks
Azure Databricks

Purpose-built for large, complex data and AI workloads. It handles high-volume engineering, machine learning, and advanced analytics when the data estate becomes computationally demanding.

Best for scale, complexity, and AI engineering
  • Move raw data from multiple systems into a single governed model
  • Support high-volume data engineering across massive datasets
  • Enable machine learning and advanced analytics beyond day-to-day BI

Platform capabilities

A logical Microsoft architecture stack
from foundation to executive action

Architecture sequence: 1) Fabric data foundation, 2) Azure infrastructure and security baseline, 3) Azure Databricks for heavy engineering, 4) Purview governance control plane, 5) Power BI semantic consumption, 6) Copilot-enabled workflows, and 7) Azure DevOps delivery discipline. Built as one operating system, not disconnected tools.

Architecture in one view

01 FoundationMicrosoft FabricUnified financial data layer
02 PlatformAzure InfrastructureSecurity, identity, and scale baseline
03 EngineeringAzure DatabricksHigh-volume processing and ML paths
04 GovernanceMicrosoft PurviewLineage, policy, and access control
05 ConsumptionPower BITrusted semantic KPI views
06 Workflow AIMicrosoft CopilotDecision support in daily work
07 DeliveryAzure DevOpsCI/CD, testing, and release control

Designed for CFO, COO, and PE operating cadence: fast close, trusted board numbers, and governed self-serve visibility.

Share this architecture

"A practical Microsoft finance data stack for PE-backed and growth-stage teams: Fabric foundation, Azure security baseline, Databricks for engineering scale, Purview governance, Power BI semantic layer, Copilot workflows, and DevOps delivery discipline."

Microsoft Fabric
Data Platform
Microsoft Fabric
OneLake as your EBITDA intelligence layer, unifying finance, operations, and procurement data across your Azure tenant. One SaaS platform, zero infrastructure overhead.
  • OneLake unified storage across all workloads
  • Direct Lake mode for real-time finance reporting
  • Lakehouse, Warehouse & Data Factory in one platform
  • Native integration with Power BI, Purview & Copilot
10-week implementation
View details
Microsoft Azure
Platform Foundation
Azure Infrastructure
Secure, scalable cloud foundation for financial workloads and controlled data movement.
  • ADLS Gen2, networking, and private endpoints
  • Managed identities and RBAC model
  • Security baseline for sensitive finance data
6-8 weeks
Details
Azure Databricks
Engineering Scale
Azure Databricks
Heavy-duty data engineering and advanced analytics for high-volume, multi-system workloads.
  • High-scale ingestion and complex transformations
  • Advanced modeling and machine learning workflows
  • Integrated with Fabric, Azure storage, and governed semantic outputs
10-14 weeks
Details
Power BI
Semantic Consumption
Power BI
Business logic encoded in semantic models so executives and operators see one consistent KPI truth.
  • Certified semantic model governance
  • Executive dashboards and self-service
  • Row-level security and embedded reporting
8 weeks
Details
Workflow AI
Microsoft Copilot
AI workflows grounded in governed data so teams move faster on variance analysis, reporting prep, and decision support.
  • M365 Copilot and Agent 365 deployment
  • Custom Copilot Studio agents
  • Readiness, governance, and adoption
10 weeks
copilot.dataqubi.com
Governance Control Plane
Microsoft Purview
Governance configured during implementation, not six months later.
  • Data catalog with automated lineage tracking
  • Sensitivity classification and labeling
  • Access policies and entitlement management
  • Compliance scanning across the Azure tenant
10-week implementation
View details
Azure DevOps
Delivery Discipline
Azure DevOps
Engineering discipline that keeps your data platform reliable and change-safe.
  • Fabric Git integration and branching strategy
  • CI/CD pipelines for Power BI and data artifacts
  • Data quality testing gates in deployment flows
  • Schema validation and automated lineage checks
6-week engagement
View details

Why Microsoft

Lower friction.
Lower execution risk.

Staying in the Microsoft ecosystem means faster adoption, cleaner governance, and fewer moving parts for teams that need reliable execution under board and lender pressure.

  • Teams already work in Excel, Power BI, and Teams, so adoption is faster and behavior change is lower.
  • Fabric, Azure, Purview, and Copilot integrate natively, reducing custom integration burden and failure points.
  • Security and identity stay in your tenant with mature controls, helping reduce compliance and lender reporting risk.
  • Your internal team can hire and scale Microsoft skills more easily than niche, fragmented stacks.

Why DataQubi

Execution over theater.
Outcomes over ambiguity.

You get one team that understands both the Microsoft stack and the operating reality of PE-backed and growth-stage companies.

Deep Microsoft stack coverage
Fabric, Azure, Databricks, Purview, Power BI, and Copilot. One integrated team that owns architecture and business context.
Focused engagements
Defined outcomes, concrete deliverables, and weekly operating cadence. No vague "transformation" program with moving goalposts.
Built for speed to value
We work with PE-backed and mid-market teams that need measurable progress in weeks, not multi-year roadmaps.

How it works

Three steps to financial visibility.
No big-bang project required.

A simple journey: diagnose, design and stand-up, then handoff with Copilot-enabled workflows. You keep ownership, governance, and momentum from day one.

01
Diagnose
We map where close, reporting, and KPI trust break down and quantify business impact.
Execs get: Financial Visibility Risk Map, baseline metrics, and a prioritized 90-day action plan.
Not required: no six-month discovery retainer.
02
Design and stand-up
We build the Fabric core, integrate required Azure and Databricks components, and publish executive-ready semantic models and dashboards.
Execs get: architecture blueprint, governed pipelines, KPI dashboards, and weekly delivery cadence.
Not required: no big-bang data lake rebuild.
03
Handoff and Copilot
We transition ownership, lock governance, and embed practical Copilot workflows into finance and operations routines.
Execs get: runbook, governance controls, enablement sessions, and self-serve operating cadence.
Not required: no indefinite dependency model.

Book a 20-minute
Financial Visibility Diagnostic

You will leave with three concrete takeaways even if we never work together:

  • Your top financial visibility failure points across close and reporting
  • A prioritized 90-day action path tied to business impact
  • A clear call on where Fabric is enough and where Databricks adds value

No slides, no sales pitch, just a whiteboard and your current reality.

Get My Financial Visibility Diagnostic See How We Deliver