Book a Discovery Call
DirectionalData LLC

The AI-Ready Semantic Layer practice.

For mid-market multi-unit operators on Snowflake or Databricks. We turn fragmented warehouses and inconsistent BI metrics into one governed semantic layer that Tableau, Power BI, Cortex Analyst, Databricks Genie, and your AI agents all read from — designed, deployed, and handed off to your team in 60 to 120 days.

Proof Points

Numbers from real engagements

3.4×
restaurant scale supported at a fast-growing QSR chain (250 → 850)
80%+
reduction in data-access times at a national mortgage finance enterprise
$5M+
in unneeded orders identified at a major supermarket distributor
10×
on-time-reporting improvement at a digital marketing agency (10% → 90%)
The Semantic Layer

One governed metric layer. Every consumer reads from it.

BI dashboards, spreadsheets, analytics tools, and AI agents all reading from the same canonical definitions — sitting on top of your data warehouse and data sources, governed end-to-end.

Diagram of the semantic layer: BI dashboards, spreadsheets and reports, analytics tools, and AI agents all flowing into a central governed semantic layer that sits above the data warehouse and data sources.
Governed · Trusted · Consistent · Scalable · Accessible · Secure
Core Engagements
Three productized semantic-layer engagements
Each is scoped from a complimentary 60-minute discovery conversation. See all five offerings →
1
Entry tier
Semantic Layer Diagnostic
A 4-week current-state audit of every metric definition in the wild, scored for drift and conflict, with a target-architecture recommendation.
Duration4 wks (fixed)
Investment$15K–$25K
2
Foundation
Foundational Semantic Layer Build
The full 90-day program: stakeholder interviews, platform selection, top-25 metric definitions, BI tool migration, and stewardship live.
Duration60–120 days
Investment$85K–$165K
3
AI overlay
AI-Readiness Semantic Layer Sprint
A 6-week sprint that benchmarks AI agent accuracy on 100 domain questions, builds the metric layer the agent needs, and hands off a runbook.
Duration6 wks (fixed)
Investment$35K–$75K
How We Work

Stabilize → Improve → Leverage

A repeatable, three-phase pattern proven across five industries and twenty-plus transformations — applied specifically to the work of building, deploying, and governing a semantic layer.

PHASE 1
Stabilize
Stop the metric bleeding. Catalog every definition in the wild. Score for drift.
PHASE 2
Improve
Build the governed layer. One definition per metric, consumed by every BI tool.
PHASE 3
Leverage
AI agents, governed self-service, predictive use cases on top of the foundation.
See the full methodology →
Industries We Serve

Five industries. One pattern of work.

Different operating contexts, the same data problems — and the same playbook for solving them.

Restaurants & Multi-Unit Retail
Multi-unit QSR · Big-box retail · Department stores
Multi-unit operations analytics, single view of customer across channels, franchise data pipelines, store-level performance reporting.
Insurance & Reinsurance
Global reinsurance · Multi-line carriers
Underwriting, claims, program-manager and carrier integration, predictive analytics for specialty lines, actuarial-data platforms.
Financial Services & Mortgage
Mortgage finance enterprises
Loss-mitigation analytics, credit-data repositories, servicer scorecard programs, self-service analytics portals at scale.
Distribution & Supply Chain
Supermarket & food-service distribution
Inventory and service-level analytics, vendor and DC performance, on-hand and on-order analysis — the work that found $5M of avoided spend at one supermarket distributor.
Marketing & AdTech
Holding-company marketing agencies
Campaign analytics, CRM and customer-touchpoint integration, weekly client reporting at scale, agency delivery operations.
Featured Case Study

Scaling BI through 3.4× growth at a fast-growing QSR chain.

Restaurants & Multi-Unit Retail

Eight years inside the BI function.

Eight years inside the chain’s BI function as it scaled from 250 to 850 restaurants. Migrated 15 TB to Snowflake on AWS. Replaced Sisense with Tableau company-wide in 120 days. Cut daily reporting SLA by 2 hours and reduced contractor spend by $200K while supporting 20% annual growth.

Read the case →
3.4×
Restaurants supported
120
Days to deploy Tableau
15 TB
Migrated to Snowflake
Founded by Dr. Dave Rogers. DBA, MIT MBA, 25 years across retail, restaurants, insurance, mortgage, and ad-tech. Adjunct Professor of analytics, statistics, and data visualization. Read the full bio at DrDaveRogers.com

Ready to talk?

Every engagement begins with a complimentary 60-minute discovery conversation. No commitment. Goal is to understand your situation, confirm whether there’s a fit, and outline what a tailored engagement could look like.