Your reporting shouldn't depend on
Manual ExportsAnd Hope.
Holmes Systems connects QuickBooks, job-costing software, and property management platforms into one dashboard that answers the question your spreadsheets can't: is this job — or this property — actually making money.
Job Profitability
Portfolio Dashboard
Avg Job Margin
24.6%
+3pts
Open Jobs
38
+6
On Budget
91%
+4%
Monthly Job Revenue
↑ 28% YoY
Connected Systems
Refresh latency
4 min
Nightly sync
All jobs reconciled
Microsoft Certified
Fabric Data Engineer Associate
Databricks Certified
Data Engineer Associate
Working stack
Not a first
data project
The experience behind these numbers is why your dashboard doesn't have to be a learning exercise for either of us.
Production models
dbt models built and maintained across silver and gold layers
Years data engineering
Building pipelines and platforms at enterprise scale
On Microsoft Fabric
Fabric in production since shortly after general availability
Platform certifications
Microsoft Fabric and Databricks data engineer associate
Most Companies Can't Trust Their Own Numbers
When a company grows, its data sprawls with it. What started as one spreadsheet export becomes a tangle of disconnected systems, undefined metrics, and reports nobody quite believes.
Holmes Systems builds the data platform that fixes these problems.
One governed source of truth, tested pipelines, and metrics defined once.
Job costs living in QuickBooks, a field app, and a spreadsheet — none of which agree
Maintenance costs and vendor invoices scattered across your PM software, spreadsheets, and text threads with vendors
Reporting that takes hours every week instead of happening automatically
Every department reports a different number for the same metric
No visibility into key metrics — job margins, portfolio performance, or which properties and projects actually pay off
What Holmes Systems Builds
Four services, one focus: a data platform your team can trust and maintain without us.
Microsoft Fabric Implementation
Lakehouse architecture built the way it holds up in production — medallion layers, governed access, and dbt pipelines that a team can actually maintain after handoff.
- Fabric Lakehouse & OneLake architecture
- Bronze / silver / gold medallion layers
- dbt on the fabricspark adapter
- Spark tuning: partitioning, caching, joins
- AI-ready feature layers & governed access
Power BI Semantic Models
The layer most Power BI problems actually live in. Star schemas and measures defined once, so every report returns the same number.
- Star schema & relationship design
- DAX measures and KPI definitions
- Cross-filter behavior that doesn't surprise you
- Certified, reusable datasets
- Report performance tuning
Source System Integration
Your operational data lives in eight systems that don't agree. We pull from accounting, job costing, dispatch, and property management systems into one warehouse that reconciles.
- Accounting: QuickBooks, Sage, Viewpoint Vista, NetSuite, SAP
- Job costing & field ops: Buildertrend, JobNimbus, ServiceTitan, Procore, HCSS
- Property & portfolio: AppFolio, Yardi, Rentvine, owner statements
- Field & asset data: SCADA, OSIsoft/AVEVA PI, Maximo, work orders
- CRM & service: Salesforce, Dynamics, ServiceNow, Jira
Data Audit & Fabric Readiness
Two weeks, fixed fee. We map where your data lives, what's breaking, and what it takes to move — and you keep the roadmap whether or not we build it.
- Source system inventory
- Data quality & reliability assessment
- Fabric migration path & architecture review
- Prioritized roadmap with cost estimates
- No-obligation deliverable
Systems Built in Production
Platforms and pipelines running today at real scale — not prototypes.
Systems delivered at enterprise scale. Client names, system names, and figures withheld where confidential.
Enterprise Revenue Data Platform
Four operational systems — CRM, ERP, project tracking, and service management — consolidated into a Microsoft Fabric lakehouse. Built the revenue, pipeline, bookings, and invoice data products, then standardized KPI definitions with Sales, Finance, and Operations so one metric meant one thing everywhere.
Two-Way CRM Reconciliation
An automation job that reads subscription and product records from a CRM, computes the expected state independently in the warehouse, then writes only the differences back — with external IDs, deduplication, date handling, logging, and guarded upserts instead of blind overwrites.
Natural-Language Data Access
An internal application on the OpenAI API that let a sales organization ask questions of CRM data directly instead of queuing requests with an analyst. Presented to executive leadership and adopted for self-service reporting.
ERP Revenue & Close Reporting
Finance tables and revenue-by-type transformations over an ERP, including transaction-line and reporting-amount handling, plus data-quality reporting so finance could see when a load looked wrong before month-end close rather than after.
How an Engagement Runs
Four steps, starting with a fixed-fee audit so you can evaluate the work before committing to a build.
Audit
Two weeks, fixed fee. We inventory every system your data lives in, assess quality and reliability, and identify where the reporting actually breaks. You leave with a costed roadmap that's yours to keep.
Architecture
Lakehouse layout, medallion layers, and metric definitions agreed before anything gets built. If Fabric isn't the right platform for your scale, this is where we tell you.
Build
Pipelines, dbt models, and semantic layer built in versioned increments with tests and data-quality checks from the first commit. You see working models each week, not a reveal at the end.
Handover
Documented models, conventional tooling, and a walkthrough with whoever owns it next. Ongoing support is available, but the platform shouldn't require us to keep running.
Who This Is Built For
Based in Houston, working with companies anywhere. The common thread is an owner or operator — running job sites, service trucks, or a property portfolio — who has outgrown spreadsheets and wants numbers they can trust without hiring a data team.
Roofing & Construction
Job costing split across QuickBooks, Buildertrend, JobNimbus, and a spreadsheet nobody trusts. We build the dashboard that answers "are we making money on this job" while the crew is still on the roof.
HVAC & Plumbing
Dispatch and work orders live in ServiceTitan; the real numbers live in QuickBooks. We connect the two so job profitability shows up without someone reconciling it by hand every month.
Property Management & Real Estate
Owner statements, maintenance costs, and occupancy scattered across AppFolio, Yardi, or Rentvine, plus spreadsheets and vendor texts. We build the portfolio view that ties it together, without replacing your PM software.
Growing GCs & Commercial Contractors
Multiple locations, multiple divisions, growth outpacing the accounting team. Procore, Sage, or Vista consolidated into one job-margin view across every crew and market.
Microsoft-Stack & Multi-Entity Companies
Power BI shops outgrowing manual extracts, or multi-entity operators reconciling mismatched ERPs and chart-of-accounts structures across acquired companies.
Not on the list?
If your reporting depends on someone remembering to run an export, we should talk.
A Data Practice, Not an Agency
Holmes Systems is a Houston-based data consultancy focused on one thing: building data platforms that hold up in production. Microsoft Fabric lakehouses, dbt pipelines, and Power BI semantic models — designed, built, and documented.
We stay deliberately small and deliberately specialized. The engineers who scope your project are the engineers who build it — no account layer, no handoff to a junior bench, no discovering mid-engagement that the expertise was on the pitch deck rather than the delivery team.
We work across the systems that operators actually run on — QuickBooks and ERPs, job-costing and dispatch platforms, property management software, and the on-prem SQL Server instances nobody wants to touch.
At a glance
- Based in
- Houston, Texas
- Engagements
- Fixed-scope audits & builds
- Certified in
- Microsoft Fabric · Databricks
- Platform focus
- Fabric, dbt, Power BI
How We Work
Define the metric once
Most reporting disputes aren't data problems, they're definition problems. Standardized KPIs in a semantic layer beat five teams each maintaining their own version.
Tested pipelines, not heroics
Versioned transformation logic, automated tests, and data-quality checks. If a load breaks, you should hear it from an alert rather than from a stakeholder.
Built to be handed over
Documented models and conventional tooling, so your team can extend the platform after the engagement ends. No dependency by design.
Day-to-day tooling
Start With a Data Readiness Call
Tell us where your data lives — QuickBooks, job-costing software, your property management platform, spreadsheets — and what reporting costs you in manual work today. If a full platform build isn't the right answer, we'll say so.
What to expect
30-minute call to walk through your current systems and reports
An honest read on whether you need a full platform, or something simpler
Scope and pricing for a 2-week fixed-fee data audit
Evening and weekend availability. No pressure, no retainer pitch.
Book a Readiness Call
Send a few details and we'll reply within 2 business days.