Three phases. Structured. Transparent. Designed to give your team clarity before a single line of code is written.
60-min structured session to understand your data landscape
Scored evaluation across 5 architecture domains
Scoped roadmap, milestones, and delivery plan
A structured 60-minute conversation to understand where your data ecosystem is today, what's blocking intelligence, and where the highest-value opportunities lie. No selling — just listening and diagnosing.
What platforms are in use? (Snowflake, Databricks, Azure, etc.) What BI tools? What orchestration?
What's not working? Slow reports, data quality issues, cloud cost overruns, AI initiatives stalled?
What does success look like? AI deployment, executive dashboards, cost reduction, compliance?
Business model, org structure, data team size, key stakeholders. Who owns data decisions?
Walk through current data architecture, modeling patterns, governance maturity, and existing pipelines.
Identify the 3 highest-leverage opportunities. What would move the needle most in 90 days?
Alignment on whether an Architecture Assessment makes sense and what scope that would entail.
Do your finance, marketing, and ops teams run on the same numbers? Or do they argue in meetings?
What decisions would you make differently if you had reliable predictive intelligence at your fingertips?
Cloud costs are often 40–60% reducible with proper architecture. Do you know where your spend goes?
A 1-page written summary of findings, identified gaps, and recommended next steps — yours to keep regardless of engagement.
If warranted, a scoped proposal for a deeper Architecture Assessment with timeline and fixed fee.
2–3 immediate actions your team can take today to improve data quality, cost, or governance — no engagement required.
A structured 2-week deep-dive across five architecture domains. We score your current state, identify the highest-risk gaps, and produce a prioritised roadmap with a clear scoping proposal for the engagement.
Once scope is agreed, we kick off with a structured 12-week delivery roadmap. Every milestone is tied to a measurable business outcome — so your stakeholders always know exactly what is being built, and why it matters.
Every Friday: what was built, what's next, any blockers — communicated in plain language your executives can read.
Every milestone is tied to a measurable business outcome — not just a technical deliverable. You always know the "why".
Scope changes are flagged immediately with options. We never expand without discussion. Fixed fees stay fixed unless scope changes.
A Medallion-based Lakehouse blueprint showing ingestion, Delta Lake storage, governance, semantic modeling, and consumption — with the exact tools we use at each layer.
Executive dashboards, regulatory KPI frameworks, and AI-led self-service analytics — all powered by the foundations we built in weeks 1–8.
Executive-grade dashboards orbiting a unified semantic core — each one pulls from the same trusted data foundation, so numbers match across every view.
The KPIs that move every industry we work in — from the metrics regulators audit to the metrics CMOs and growth teams optimise on. Clean data turns these from quarterly reviews into real-time decisions.
Total reportable accidents per million miles driven.
DOT / FMCSADriver fatigue & rest-break compliance tracking.
FMCSASpeeding, harsh braking, improper lane changes — via telematics.
FMCSA · CSAMechanical failures and service disruptions, segmented by route.
FTA · State DOTDiagnostic trouble codes & recurring fault patterns across the fleet.
Fleet OpsDaily vehicle inspection reports and outstanding defects.
FMCSARandom testing compliance & clearinghouse query rate.
DOT · ClearinghouseMPG, CO₂ per shipment — for environmental reporting.
EPA · SmartWayIdle minutes driving inefficiency and emissions reporting.
EPA · Fleet OpsComposite of DOT inspections, violations, crashes, & driver fitness.
FMCSA · CSAAvailability × Performance × Quality — the master metric.
ISO · Lean% of units produced correctly the first time, no rework.
ISO 9001Average time to complete one unit — the pulse of the line.
Lean · Six SigmaUnits produced per hour / shift / day. Capacity in motion.
ProductionActual vs. potential output — reveals expansion headroom.
Finance · Ops% of customer orders shipped by promised date.
Customer SLA% of defective output — direct hit to margin and quality.
ISO · QualityHow many times inventory sells through per period.
FinanceWorkplace injuries per 200K hours — OSHA mandate.
OSHAkWh & CO₂ per unit produced — ESG reporting.
EPA · ESGReturn on ad spend across every channel and campaign.
PerformanceCost per thousand impressions — efficiency of paid reach.
MediaCost per click — what you pay to bring intent on-site.
Performance% of sessions that complete the target action.
PerformanceOut-of-stock signal that suppresses paid spend automatically.
InventorySessions, users, new vs returning, by source.
GA4Lifetime value — the metric that decides whether a CPA is good.
StrategicCost per acquired lead / customer — the bottom of the funnel.
PerformanceHigh-LTV, high-quality leads (HQL) are weighted as the priority — full LTV-aware funnel maths to follow.
Installs from Google Play, segmented by region and campaign.
Play StoreInstalls from the App Store, segmented by region and campaign.
App StoreActive interaction rate in first 30 days post-install.
RetentionPersistent-user signal at 60 days — early loyalty read.
RetentionTrue power-user cohort, the basis for LTV modelling.
RetentionApp deletions inside 30 days — first-impression failure rate.
ChurnDrop-offs in days 30-60 — engagement-loop failure.
ChurnLong-tail deletion — value-realisation failure.
ChurnVolume of intent across pages, modules, and CTAs.
GA4Interaction rate per impression of a creative or module.
GA4% of sessions that add-to-cart but don't check out.
E-comCountry, state, city — paired with revenue per region.
GA4Google · Bing · Yahoo · direct · referral · social.
GA4Which step lost them — and was it UX or CTA copy?
UX · CROEach step is annotated with the dominant failure mode so the fix lands in the right place.
Sponsored Products, Brands, and Display — by ASIN and campaign.
Amazon AdsWalmart Connect spend by SKU and category.
Walmart ConnectSearch-term reports, bid efficiency, share of voice.
Search AdsOrganic + sponsored rank for priority terms.
MerchandisingA+ content, imagery, copy — what's converting on PDP.
ContentBuy-box %, stock-out events, and ad eligibility.
MarketplaceMaria led Seagate's full Amazon programme — product placement, A+ design, and copy — driving search rank and ad efficiency across the storage portfolio. Detailed results write-up will live in the case-studies section.
Impressions delivered, household penetration, frequency curve.
MVPDAddressable segments, lookalike modelling, and overlap analysis.
AddressableBrand and sales lift attributable to MVPD spend.
MeasurementCPP, CPM, and effective CPA against household-level outcomes.
EfficiencyMVPD measurement is a frontier area — we're building out the metric definitions, attribution model, and a full client write-up. This panel will expand once the framework is finalised.
Because the data foundation is clean, the semantic layer is sound, and governance is in place — executives can ask questions in natural language and get trusted answers in seconds.
Six enterprise-grade frameworks layered together so your data stays trustworthy, auditable, and compliant — by design, not by exception.
The "owner's manual" we hand over so your technical team can run, govern, and grow the data stack without depending on us. This is the transition from consultant-led development to client-led maintenance — the repository of knowledge that keeps pipelines running, errors recoverable, and architecture scalable.
The day-to-day "what to do" guides for the team running the platform.
The reference material analysts and engineers reach for to understand the system.
The control layer your auditors, security team, and data stewards will ask for.
The visibility your finance and platform teams need to keep cloud spend predictable.
The full OBT Client Handover Package — a real (anonymised) example showing every document above with sample data.
A structured 4-week programme that takes your team from platform hand-off to genuine self-sufficiency. Built around the stack we deployed (Snowflake · dbt · Databricks) and tailored to your team's existing skills.
Live tour of the architecture, data dictionary, and the runbooks your team will own. Q&A with the build team.
Your team runs the pipelines under our supervision — incident response drills, scheduled-job triage, and production deployment.
Semantic-layer self-service training: how to query the gold layer, build trusted dashboards, and request new metrics correctly.
Your team operates the platform end-to-end. We're on standby. We exit when the dashboard signs you delivered three production changes without us.
The branded Team Enablement Programme — full curriculum, learning objectives, success criteria, and a sample timeline.