Data Foundation
Fix your data layer before your dashboards or AI models. We build semantic models, certified metric definitions, and data quality frameworks.
What this service covers
- data foundation consulting
- semantic model design
- metric definitions
- data quality consulting
- data layer
- business glossary
- data modeling
Proof: client outcomes from this practice
- We recovered $4.8M a year in misrouted claims by lifting member match accuracy from 75 to 94 of every 100 records, restarting three stalled ML pilots. , Express Scripts
- Implemented a data governance framework for four product lines that cut audit prep time from six weeks to four days and prevented $1.8 million in regulatory fines. , Informatica
Frequently asked questions
What is a data foundation and why does it matter?
A data foundation is the semantic layer, metric definitions, and data quality infrastructure that sits between your raw data sources and your dashboards or AI models. Without it, every downstream system produces different numbers. With it, every team works from the same certified truth.
How long does a data foundation engagement take?
Most data foundation engagements run 8 to 16 weeks depending on scope. We deliver a statement of work with defined milestones so you know exactly what you are getting and when.
Do we need to replace our data platform first?
No. In most cases we fix the semantic layer and metric definitions on top of your existing platform. Platform replacement is rarely the right first step and often the most expensive mistake organizations make.
What does a certified metric definition actually mean?
A certified metric is one that has a single agreed-upon definition, a documented owner, a known lineage from source to report, and a governance process for change management. When a metric is certified, every dashboard and every AI model that uses it produces the same number.
Request the 30-day Analytics Truth Audit to scope this engagement for your environment.