Your Data Exists. The Question Is Whether You Can Use It.
Pipelines, warehouses, and dashboards that turn scattered operational data into one set of numbers your team trusts. Decisions get made on what's actually happening, not on what someone pulled together this morning.
Most organizations at the growth stage have a data problem that looks like a reporting problem. Finance is pulling from one system, operations is running reports from another, and the CEO is looking at a dashboard that was accurate last quarter but nobody's sure about today. The real issue is upstream: there's no central place where data lands, gets cleaned, and gets structured for analysis. Every report is a one-off extraction. Every analysis requires a data pull. Every decision is made on numbers someone had to assemble by hand.
Analytics infrastructure is the fix. It means building the pipelines that move data from your operational systems, including your EHR, your ERP, your CRM, and your billing platform, into a central cloud data warehouse where it's clean, structured, and available for reporting. It means building the transformation layer that makes raw operational data analytically useful. And it means building the dashboards and reporting layer on top that lets the right people see the right numbers without filing a ticket to the data team.
We build this stack for companies that are serious about data but aren't yet running a 10-person analytics function. We scope it to what the business actually needs, not a Fortune 500 data platform, but a reliable, maintainable system that puts current numbers in front of operators and executives. The point isn't the infrastructure. The point is the capacity it creates: hours your team gets back to ask the questions that move the business.
How We Build Your Analytics Stack
Discovery and Current State Assessment
We map every data source that matters: which systems are authoritative, which are duplicative, what's already being exported or reported, and where the gaps are. We look at what decisions your operators actually make and what data they need to make them well. The output is a current-state data map and a prioritized list of analytical problems worth solving first.
Warehouse Design and Cloud Setup
The data warehouse is the center of gravity for the stack. We select and configure the cloud warehouse that fits your scale and budget, typically Snowflake, BigQuery, or Redshift depending on your existing cloud footprint. We design the schema across raw, staging, and analytics-ready layers so the warehouse is structured for both reliability and performance.
Pipeline Development and Source Integration
We build ingestion pipelines for each data source, including EHRs, billing systems, ERPs, CRMs, flat file exports, and APIs. We use managed tools where they reduce complexity (Fivetran, Airbyte) and write custom connectors where source systems require it. Pipelines run on schedule, with monitoring and alerting so you know immediately if something breaks.
Transformation and Data Modeling
We build the transformation layer using dbt or equivalent, defining business logic, creating dimension and fact tables, and building the analytical models that your reports will run against. Every transformation is documented and version-controlled. When the logic changes, we change it in one place, not across 40 spreadsheets.
Dashboard and Reporting Layer
We build the dashboards in your BI tool of choice, including Tableau, Power BI, Looker, or lighter tools like Metabase depending on your user base and budget. Dashboards are designed for operators, not data teams. Clear, opinionated, and focused on the decisions they support.
Handoff, Documentation, and Ongoing Support
We document every pipeline, transformation, and dashboard at handoff. We train your internal owners on the system architecture. You'll have everything you need to run it independently, and we're available when you need to extend or modify the system.
Capabilities
What we build, and what we know how to build well.
Source-to-Warehouse Pipeline Development
We build ingestion pipelines from every major operational system, including EHRs, ERPs, CRMs, billing platforms, flat file exports, and REST APIs. Pipelines run on schedule with monitoring and alerting. Data lands in your warehouse reliably without manual intervention.
Cloud Data Warehouse Architecture
We design and deploy cloud warehouse environments on Snowflake, BigQuery, or Redshift, structured with proper layering (raw, staging, marts) so the foundation grows with the business and doesn't need a rebuild every time you add a source.
Data Modeling and Transformation (dbt)
We build the transformation layer that converts raw operational data into analytically useful models. Business logic is codified, documented, and version-controlled, not buried in spreadsheet formulas or ad hoc SQL.
BI Dashboard Development
Dashboards designed for the operators and executives who will actually open them. We build in Tableau, Power BI, Looker, and Metabase, and we'll tell you honestly which one fits the situation.
EHR and Healthcare Data Integration
We've built pipelines from Athena, Epic, eClinicalWorks, Kareo, and others. We know where the data lives, what the quirks are, and how to get it into a warehouse in a usable format.
Who We Serve
Growth-Stage Companies
Series A through PE-backed companies where operators are assembling numbers by hand every week and finance is spending more time pulling data than reading it.
Multi-Site Healthcare Operators
Multi-site practices and groups that need a single view of clinical and financial performance across EHRs, billing systems, and practice management platforms.
PE-Backed Portfolio Companies
Portfolio companies expected to produce PE-standard reporting without the underlying data infrastructure to do it reliably.
In practice
Recent Work
Anonymized engagements where we delivered this service. Client details kept confidential.
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Stop Pulling Reports by Hand.
Send us the report your team rebuilds every week. We'll tell you what it would take to make it run itself.
Talk to Us About Your Data Stack