Atlanta Data Consulting
Atlanta Data Consulting for Complex, Growing Businesses
Data problems in growing companies rarely arrive all at once. Systems accumulate. An acquisition brings in another ERP. Divisions build their own reporting because waiting on a central team takes too long. Then leadership is looking at two versions of the same number and has to decide which one to act on.
Stratiform Group designs the data architecture underneath that problem. We work with private equity firms, mid-market leadership teams, and the portfolio companies they own across metro Atlanta, and with organizations nationally.
Atlanta is home base, not a boundary.
Working Across the Metro, In Person Where It Counts
Atlanta is a spread-out market. A sponsor sits in Buckhead. The portfolio company it just bought operates out of Alpharetta, with a distribution facility off I-75 in Cobb County and a finance team in Perimeter. Coordinating a data project across those locations by video call is possible. But complex discovery and architecture discussions can move faster when the right people are in the same room.
Being based here means we can be in more than one of those rooms in the same week.
That matters most in three situations. Discovery sessions go faster when finance and operations are at the same table and can correct each other in real time. Architecture sessions benefit from a whiteboard when two departments define the same metric differently, and neither has noticed. And integration planning after a deal often benefits from bringing together people who have never met before the transaction closed.
We work throughout the metro, including Buckhead, Midtown, Perimeter, the Cumberland and Galleria corridor, and Alpharetta and North Fulton.
We are not limited to Atlanta. Proximity is something we offer when it adds value, not a condition of working together.
The Data Problems Behind Atlanta’s Major Industries
Atlanta’s business base concentrates in a handful of sectors, and each one tends to produce a recognizable kind of data problem.
Financial Services, Investment Banking & Payments. High transaction volume moving across processors, gateways, core systems, and ledgers, where the reconciliation logic sits in spreadsheets that one person understands, and nobody has documented.
Logistics & Distribution. Operational data split between warehouse systems, transportation management platforms, and carrier portals that were never built to report against each other, so service and cost performance get assembled by hand.
Healthcare Services. Multi-site groups put together by acquisition, where each location arrived with its own practice management and billing system, and its own definition of a completed visit.
Industrial, Field Service & Business Services. Work orders, dispatch, and job costing spread across a service management platform and an accounting system that do not share a job identifier, so utilization and margin by job get reconstructed after the period closes.
PE-Backed & Multi-Entity Companies. Every entity kept its own chart of accounts and its own KPI definitions, so consolidated reporting is a monthly manual exercise rather than a system output.
This range reflects the combined Stratiform Group and WeGotCode team. Our principals include a former chief executive of a healthcare services company, a leader who ran logistics and engineering operations for a national delivery business, and senior experience inside payments and financial services technology firms. The problem pattern holds across these sectors even when the underlying systems differ, which is why we describe our work by that pattern rather than by vertical.
Platform Decisions Come After the Architecture
Most data initiatives begin with a product. Move to the cloud. Replace the reporting tool. Add another integration. Those may end up being the right steps, but starting there tends to add a layer of technology on top of a structural problem rather than resolving it.
We start by mapping how information moves through the organization, where systems lose track of each other, how reporting is currently assembled, and what leadership actually needs to see. Technology recommendations follow from that. The result is a defined enterprise data architecture that the platform choice then serves.
In practice, most of this work lands on Microsoft Fabric and Databricks, with Snowflake where the environment calls for it, Azure underneath, and Power BI at the reporting layer. We work across all of them. Which one is right depends on what the architecture requires, and that order does not reverse.
Multi-Entity Reporting in an Acquisitive Market
Atlanta has a deep bench of sponsors and acquisitive mid-market companies, which means a large share of the data work here starts with a transaction rather than a technology decision.
Acquired companies almost never arrive on compatible systems. Finance runs on a different platform. Operational tools do not talk to each other. KPI definitions differ in ways that only surface when someone tries to combine two reports. The consolidation work falls to a controller with a spreadsheet, at exactly the point when the sponsor most needs a clear read on performance.
We work in private equity-backed and multi-entity environments to build a repeatable structure for connecting acquired businesses, rather than forcing every company into an immediate replacement project. Our post-acquisition integration work covers how that structure gets built and what it changes for reporting.
What Leadership Sees and What the Systems Actually Hold
Executives do not need more data. They need numbers consistent enough to act on without a side conversation about where they came from.
When reporting depends on manual exports, disconnected systems, or metric definitions that vary by department, a well-designed dashboard mostly makes unreliable information look more convincing. The gap between what leadership sees and what the systems hold does not close by changing the visualization layer.
We look at where data originates, how it moves, how metrics are defined, and where inconsistencies enter.
That work usually reaches down into the pipelines and storage beneath the reporting layer, because that is generally where the inconsistency starts.
FAQs
What does an Atlanta data consulting firm do?
Does Stratiform only work with companies in Atlanta?
What is the difference between a data consulting firm and a BI implementation partner?
When should a company bring in outside help rather than hiring internally?
Hiring makes sense when the work is continuous and the requirements are already understood. Outside help tends to fit better when the question is what the environment should look like, when the answer needs to come faster than a hiring cycle allows, or when an internal team is capable but fully committed to running the systems already in place.
Metric definitions, ahead of systems. Two companies reporting revenue or headcount on different definitions will not produce comparable portfolio reporting no matter how well their platforms are connected. Agreeing what each number means, then designing the architecture that produces it consistently, avoids rebuilding the reporting layer after the definitions get settled.
Which platforms does Stratiform work with?
When the Data Environment Starts Slowing the Business Down
Data problems rarely stay technology problems. They become reporting problems, then integration problems, then decision-making problems.
If fragmented systems, manual reporting, inconsistent metrics, or acquisition-related complexity are limiting confidence in the numbers, the next step may not be another platform. It may be understanding the structure underneath it.