Our story

Built by someone
who sat in the seat

DataQubi was built from 20+ years across enterprise architecture, data & analytics leadership, private equity operating environments, and academic advisory work, including three years as Chief Data & Analytics Officer at Artera Services.

The problem wasn't technology. Every company had Azure. Most had Power BI. Several were mid-migration to Microsoft Fabric. The problem was that the underlying financial data (vendor records, invoice history, AR aging) was dirty in ways that compounded quietly until month-end, when the chaos became visible.

"We had Power BI. We had good analysts. The CFO still didn't trust the number on the dashboard; and neither did anyone else in the room."

CFO · PE-backed portfolio company · $220M revenue

That conversation happened more than once. DataQubi is the firm we built in response: a focused engagement that hardens financial data inside your own Azure environment, delivers findings in 14 days, and leaves your team with numbers they can actually stand behind.

The cost of doing nothing

What dirty financial data
actually costs

These aren't projections. They're what we found (consistently) across PE-backed portfolios at the $50M–$500M revenue band.

$300K–
$600K

Recoverable duplicate payments

Hidden in plain sight when the same vendor exists under multiple names. Amounts are often small enough to pass AP review individually. They accumulate.

Typical finding · $200M revenue company

5–7 Days

Month-end close delay

Finance teams reconciling data that shouldn't need reconciling. The close drags. Auditors wait. The board gets numbers a week late, every quarter.

Median across 6-company portfolio

8–15%

Supplier master duplication rate

Acquisitions layer new ERP instances onto existing ones. Vendor records merge imperfectly. The same supplier appears under four names with three addresses.

Average rate across post-acquisition environments

The pattern

The same four problems. Every company. Every ERP.

Not theory. This is what we encountered in the portfolio, and what we built DataQubi to solve.

Duplicate vendor masters: everywhere

Acquisitions layer new ERP instances onto existing ones. Vendor records from acquired companies merge imperfectly. The same supplier appears under four names with three addresses and two tax IDs. AP teams know it's broken. Nobody owns fixing it.

Working capital metrics nobody trusted

DSO is 47 days in the Power BI dashboard. The CFO thinks it's closer to 55. The controller has a spreadsheet that says 61. All three are right: they're pulling from different data. Benchmarking across business units is impossible when the denominators don't agree.

Duplicate payments hiding in plain sight

When vendor #4821 and vendor #4821-A are both active, and both receive payment runs, some invoices get paid twice. The amounts are often small enough to clear AP review. They accumulate. In a $200M company, this typically represents $300K–$600K in recoverable cash.

Month-end close delayed by reconciliation chaos

Finance teams spend the last week of every month reconciling data that shouldn't need reconciling. The close drags. Auditors ask for documentation that requires manual assembly. The problem isn't process: it's that the data underneath the process isn't clean.

Background & affiliations

The perspective behind the work

DataQubi's methodology is shaped by cross-sector experience: enterprise transformation, PE operating models, higher-education advisory, and CDO community thought leadership.

Artera Services · CD&R Portfolio

Chief Data & Analytics Officer

Led data strategy across six PE-backed operating companies with distinct ERP environments and integration requirements. This chapter informed DataQubi's operating model for practical, finance-ready data execution.

Private Equity Operations

University of Georgia · Terry College

Advisory Board & Faculty

Member of the MS Business Analytics Advisory Board, contributing to curriculum, experiential learning, and industry placement. Previously taught Business Intelligence and Data Storytelling to MBA candidates.

Academic Advisory

CDO Magazine

Global Editorial Board Member

Contributes to the Chief Data Officer community on AI-resilient data architecture, Microsoft Fabric, and financial data governance for enterprise and PE-backed environments.

Thought Leadership

How we work

Four commitments that don't move

Not aspirational values. Structural constraints built into how every engagement is designed and delivered.

Your data never leaves your tenant

Every DataQubi engagement runs inside your Azure environment. We deploy into your Microsoft Fabric workspace with read-only ERP access. Nothing is transmitted to external servers. No exceptions. This is architecture, not policy: the data has no path out.

First value in seven days, not seven months

The 14-day engagement is deliberate. PE-backed companies don't have runway for long implementations. Finance teams need findings they can act on before the next board meeting. We scope to deliver duplicate findings by Day 7, before the engagement is half complete.

We don't replace what's working

DataQubi doesn't touch your ERP. It doesn't replace your reporting stack. It doesn't require a new BI tool. We harden the data that feeds the systems you already have, so your existing investments start performing the way they were supposed to.

Audit lineage is non-negotiable

Every deduplication decision, every classification, every anomaly flag is logged with a full lineage trail. Finance teams can trace any output back to its source. CFOs and PE operating partners need to defend their numbers; we make that possible.

Get in touch

Where to find us

We work with companies across the US. Most engagements start with a 20-minute call: no slides, no sales handoff, just a direct conversation about your environment.

Headquarters

DataQubi, LLC

3133 Maple Dr NE, Ste 240
Atlanta, GA 30305, USA

Serving mid-market and PE-backed companies across North America. Engagements are delivered remotely; your data stays in your Azure tenant throughout.

Start a conversation

20-minute strategy call

Talk directly to Balaram, the person who runs every engagement. We'll look at your environment and tell you where to start. No pitch deck. No hand-off to a sales team.

Schedule a Call

Direct line

For partnership inquiries, press, or technical questions about Microsoft Fabric and the DataQubi platform.

info@dataqubi.com

Phone

Main line

For direct calls during business hours (ET).

404-590-7861

Microsoft Practice

Full platform engagements

Beyond financial data hardening: Fabric implementation, Power BI, Copilot, Microsoft Foundry, Purview. Broader data platform needs start here.

View Microsoft Practice

Built by someonewho sat in the seat

What dirty financial dataactually costs