Home Services Insights Our Approach About Contact Assess Your Readiness → Book a Session

Our Engagement
Methodology

Three phases. Structured. Transparent. Designed to give your team clarity before a single line of code is written.

Phase 1: Discovery Phase 2: Assessment Phase 3: Kick-off
01

Initial Discovery Call

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.

📋 Pre-Call Intake (Sent in Advance)

1
Current Stack Overview

What platforms are in use? (Snowflake, Databricks, Azure, etc.) What BI tools? What orchestration?

2
Pain Points & Blockers

What's not working? Slow reports, data quality issues, cloud cost overruns, AI initiatives stalled?

3
Strategic Goals (12 Months)

What does success look like? AI deployment, executive dashboards, cost reduction, compliance?

🎯 Discovery Call Agenda (60 min)

A
0–10 min: Context Setting

Business model, org structure, data team size, key stakeholders. Who owns data decisions?

B
10–35 min: Architecture Audit

Walk through current data architecture, modeling patterns, governance maturity, and existing pipelines.

C
35–50 min: Priority Mapping

Identify the 3 highest-leverage opportunities. What would move the needle most in 90 days?

D
50–60 min: Next Steps

Alignment on whether an Architecture Assessment makes sense and what scope that would entail.

❓ Key Diagnostic Questions

Q
"Is there one version of truth?"

Do your finance, marketing, and ops teams run on the same numbers? Or do they argue in meetings?

Q
"What would AI unlock for you?"

What decisions would you make differently if you had reliable predictive intelligence at your fingertips?

Q
"What does your cloud bill look like?"

Cloud costs are often 40–60% reducible with proper architecture. Do you know where your spend goes?

📤 Discovery Call Output

Summary Brief (Within 48 hrs)

A 1-page written summary of findings, identified gaps, and recommended next steps — yours to keep regardless of engagement.

Architecture Assessment Proposal

If warranted, a scoped proposal for a deeper Architecture Assessment with timeline and fixed fee.

Quick-Win Recommendations

2–3 immediate actions your team can take today to improve data quality, cost, or governance — no engagement required.

02

Architecture Assessment

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.

🏗️ Data Architecture & Modeling

Schema DesignScored 1–5
Semantic Layer MaturityScored 1–5
Pipeline ArchitectureScored 1–5

🔒 Governance & Data Integrity

Data Quality FrameworkScored 1–5
Lineage & ObservabilityScored 1–5
Access Control & RBACScored 1–5

☁️ Cloud Infrastructure & Cost

Cloud Cost EfficiencyScored 1–5
Infrastructure ScalabilityScored 1–5
Disaster RecoveryScored 1–5

🤖 AI & Analytics Readiness

Feature Store / ML PipelineScored 1–5
Predictive Model InfrastructureScored 1–5

📊 BI & Reporting Maturity

Dashboard Coverage & TrustScored 1–5
Self-Service AdoptionScored 1–5

📤 Assessment Deliverables

Architecture Scorecard — Domain-by-domain scores with benchmark comparisons against Fortune 500 norms
Gap Analysis Report — Prioritised list of architecture gaps, risks, and quick wins with effort/impact ratings
Technology Stack Recommendations — Platform selection guidance based on your scale, budget, and roadmap
Scoping Proposal — Fixed-fee, phased engagement scope for the full architecture build with clear milestones
03

Engagement Kick-off & Roadmap

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.

Weeks 1–2

Foundation Sprint

Stakeholder alignment & sign-off Source system access & credentials Architecture design sessions Environment setup & tooling
Weeks 3–5

Data Architecture Build

Core data model design Pipeline engineering (ETL/ELT) Governance framework setup Data quality monitoring live
Weeks 6–8

Semantic Layer & Governance

Semantic model deployment Access control & RBAC Lineage documentation First stakeholder review
Weeks 9–10

Intelligence Layer

Executive dashboards (Power BI / Tableau) KPI framework deployed AI feature store foundations Performance optimization
Weeks 11–12

Handoff & Enablement

Team training & documentation Runbook & maintenance guide Final stakeholder presentation Ongoing support plan
📐Architecture Blueprint
📊Executive Dashboards
🔒Governance Framework
📋Runbook & Docs
🤖AI-Ready Data Layer
🎓Hand-off & Team Enablement
Our Standards

What to Expect From Every OBT Engagement

📅

Weekly Status Updates

Every Friday: what was built, what's next, any blockers — communicated in plain language your executives can read.

🎯

Outcome-Tied Milestones

Every milestone is tied to a measurable business outcome — not just a technical deliverable. You always know the "why".

🔄

No Surprises Policy

Scope changes are flagged immediately with options. We never expand without discussion. Fixed fees stay fixed unless scope changes.

The 30 / 60 / 90 Road Map

How we turn an engagement into momentum. Every deliverable is mapped to our five architecture pillars and tracked in a single live master file — so you always know what shipped, what's next, and where the architecture stands. No Jira, no Confluence, just weekly clarity.

Below is a sample 30-day delivery plan — the same structure we run for every client. Each of our five architecture pillars carries its own set of deliverables for the 30, 60 and 90-day phases, and the developers simply update them as they go. The result is an agile, lean engagement where the artefacts are the status report.

🗂️

A single source of truth

Notion and Figma artefacts for every client, phase and pillar live in one master file you can open any time — no tool-hopping.

Updates without overhead

Weekly stand-up snapshots replace ticket admin. The deliverables update in place, so progress is always current.

🤖

AI-leveraged delivery

We use AI to keep implementation agile, lean and efficient — getting you to reliable advanced analytics faster.

Sample shown: the first 30 days for a DirecTV foundation engagement. Each pillar below lists what lands by day 30.

Master File · Weekly Snapshot

What a client snapshot actually looks like

These are the working artefacts behind the 30-day plan, rebuilt here as live views. In a real engagement each one is a Notion or Figma file linked inside the client master file — opened in seconds for any weekly stand-up.

DirecTV_Foundation_30day.fig · Medallion Architecture Blueprint Pillar 01 · Day 14
🥉 BRONZE · RAW INGESTION
stg_raw_subscriberFivetran → Snowflake · CRM · hourly
stg_raw_viewershipACR events · 68M HH · streaming
stg_raw_billingBilling platform · txn level · daily
stg_raw_ad_impressionsDSP + ad server · impression log
4 staging tables · full fidelity
🥈 SILVER · CLEANSED & CONFORMED
int_subscriber_baseDeduped · tenure · churn flag
int_viewership_aggSession rollup · affinity index
int_billing_cleanLTV calc · ARPU · payment health
int_ad_performanceCampaign rollup · reach · frequency
4 int models · dbt · DQ tested
🥇 GOLD · BUSINESS-READY OBTs
dim_subscriber_360OBT · segment · LTV tier · churn
fact_subscriber_eventsStar schema · all event types
fact_ad_performanceMVPD KPIs · reach/freq/lift/CPM
dim_content_catalogGenres · networks · metadata
4 gold tables · Power BI ready · SLA <4min
Data_Product_Catalog Pillar 02
Data ProductLayerOwnerStatus
subscriber_360GoldData EngLive
ad_performanceGoldAnalyticsBuild
viewership_aggSilverData EngLive
content_catalogGoldData EngPlanned
billing_cleanSilverData EngLive
Document_Registry All pillars
DocumentPillarLinkStatus
Architecture Blueprint01Figma ↗Approved
ERD & Medallion Spec01Notion ↗Draft
Governance & RBAC Matrix02Notion ↗Approved
Cloud Cost Baseline03Notion ↗Approved
KPI Dictionary05Notion ↗Draft
Sprint_Tracker · 30-Day Foundation Week 3 of 4
Stand up Snowflake landing zone Pillar 03 · Cloud Infrastructure
Cloud Eng
Done
Bronze ingestion — 4 source systems Pillar 01 · Data Architecture
Data Eng
Done
Silver dbt models + DQ tests Pillar 01 / 02
Data Eng
In progress
Subscriber 360 gold OBT Pillar 01 / 05
Analytics
In progress
AI readiness scorecard Pillar 04 · AI & Analytics
Lead Architect
Planned

This snapshot uses sample DirecTV data for demonstration. In a live engagement, every cell links to the real Notion or Figma artefact in the client master file — the ERD and architecture blueprint are standardised per client and updated as the team ships.

The KPIs That Move Every Industry We Work In

From the metrics regulators audit to the metrics CMOs and growth teams optimize on. Clean data turns these from quarterly reviews into real-time decisions. Select an industry:

Required by DOT / FMCSA for fleet operators and state transportation agencies. Miss these and you're in non-compliance. Track them in real time and you reduce incidents, lower insurance, and pass audits effortlessly.
🚨
DOT Reportable Accidents

Total reportable accidents per million miles driven.

DOT / FMCSA
⏱️
Hours of Service (HOS) Violations

Driver fatigue & rest-break compliance tracking.

FMCSA
⚠️
Driver Safety Violations

Speeding, harsh braking, improper lane changes — via telematics.

FMCSA · CSA
🚌
Bus Failures by Route

Mechanical failures and service disruptions, segmented by route.

FTA · State DOT
🔧
Check Engine Failures

Diagnostic trouble codes & recurring fault patterns across the fleet.

Fleet Ops
🛠️
Driver Maintenance (DVIR)

Daily vehicle inspection reports and outstanding defects.

FMCSA
🧪
Drug & Alcohol Testing Rates

Random testing compliance & clearinghouse query rate.

DOT · Clearinghouse
Fuel Efficiency / Emissions

MPG, CO₂ per shipment — for environmental reporting.

EPA · SmartWay
🕒
Vehicle Idle Time

Idle minutes driving inefficiency and emissions reporting.

EPA · Fleet Ops
📋
CSA Score (Safety & Accountability)

Composite of DOT inspections, violations, crashes, & driver fitness.

FMCSA · CSA
Core KPIs tracked by ISO 9001, OSHA, and industry regulators. These are the metrics that separate high-performing manufacturers from the rest — and what auditors pull first.
⚙️
Overall Equipment Effectiveness (OEE)

Availability × Performance × Quality — the master metric.

ISO · Lean
First Pass Yield (FPY / FTT)

% of units produced correctly the first time, no rework.

ISO 9001
Cycle Time

Average time to complete one unit — the pulse of the line.

Lean · Six Sigma
📈
Throughput

Units produced per hour / shift / day. Capacity in motion.

Production
📊
Capacity Utilization

Actual vs. potential output — reveals expansion headroom.

Finance · Ops
📦
On-Time Delivery (OTD)

% of customer orders shipped by promised date.

Customer SLA
♻️
Scrap / Rework Rate

% of defective output — direct hit to margin and quality.

ISO · Quality
🔄
Inventory Turnover

How many times inventory sells through per period.

Finance
🦺
Recordable Incident Rate (TRIR)

Workplace injuries per 200K hours — OSHA mandate.

OSHA
🌿
Energy / Emissions per Unit

kWh & CO₂ per unit produced — ESG reporting.

EPA · ESG
The metrics CMOs and growth leads live in. Built around a clean acquisition funnel where high-LTV, high-quality leads are the optimization target — not raw lead count.
💰
ROAS

Return on ad spend across every channel and campaign.

Performance
📐
CPM

Cost per thousand impressions — efficiency of paid reach.

Media
🖱️
CPC

Cost per click — what you pay to bring intent on-site.

Performance
🎯
Conversion Rate

% of sessions that complete the target action.

Performance
📦
OOS

Out-of-stock signal that suppresses paid spend automatically.

Inventory
🚦
Traffic

Sessions, users, new vs returning, by source.

GA4
💎
LTV

Lifetime value — the metric that decides whether a CPA is good.

Strategic
💵
CPA

Cost per acquired lead / customer — the bottom of the funnel.

Performance
Customer Acquisition Funnel

High-LTV, high-quality leads (HQL) are weighted as the priority — full LTV-aware funnel maths to follow.

Impressions5.2M
LQL — Low-Quality Leads8,200
HQL — High-Quality Leads ★2,140
Leads1,180
Acquired Customers312
CPA — Cost Per Acquired Lead$184
App-level health: where users come from, whether they stay, and when they delete. Tracked against 30 / 60 / 90-day windows for honest cohort reads.
🤖
Android Downloads

Installs from Google Play, segmented by region and campaign.

Play Store
🍎
iOS Downloads

Installs from the App Store, segmented by region and campaign.

App Store
30-Day Engagement

Active interaction rate in first 30 days post-install.

Retention
📈
60-Day Engagement

Persistent-user signal at 60 days — early loyalty read.

Retention
🏆
90-Day Engagement

True power-user cohort, the basis for LTV modelling.

Retention
🗑️
30-Day Churn

App deletions inside 30 days — first-impression failure rate.

Churn
📉
60-Day Churn

Drop-offs in days 30-60 — engagement-loop failure.

Churn
90-Day Churn

Long-tail deletion — value-realisation failure.

Churn
Where the funnel actually breaks — wired into GA4 and segmented by region, channel, and creative. Drop-off attribution distinguishes UX defects from CTA / messaging defects.
🖱️
Clicks

Volume of intent across pages, modules, and CTAs.

GA4
📊
Engagement / Display

Interaction rate per impression of a creative or module.

GA4
🛒
Cart Abandonment

% of sessions that add-to-cart but don't check out.

E-com
🌍
Traffic by Region

Country, state, city — paired with revenue per region.

GA4
🔎
Channel Mix

Google · Bing · Yahoo · direct · referral · social.

GA4
🧭
Drop-off Attribution

Which step lost them — and was it UX or CTA copy?

UX · CRO
Funnel Drop-off — UX vs CTA

Each step is annotated with the dominant failure mode so the fix lands in the right place.

Landing — visit100%
Product page (UX-driven drop)64%
Add to cart (CTA-driven drop)38%
Checkout — info entry22%
Purchase11%
Spend efficiency on aggregator platforms — Amazon, Walmart, and the keyword-driven search-ad layer that decides whether 3rd-party sellers ever get found.
🅰️
Amazon Ad Spend

Sponsored Products, Brands, and Display — by ASIN and campaign.

Amazon Ads
🅆
Walmart Ad Spend

Walmart Connect spend by SKU and category.

Walmart Connect
🔑
Keyword Performance

Search-term reports, bid efficiency, share of voice.

Search Ads
📍
Product Placement

Organic + sponsored rank for priority terms.

Merchandising
🎨
Creative Performance

A+ content, imagery, copy — what's converting on PDP.

Content
📦
3P Seller Visibility

Buy-box %, stock-out events, and ad eligibility.

Marketplace
Case Study · Coming Soon
Seagate — End-to-End Amazon Presence

Maria 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.

Campaign effectiveness inside Multichannel Video Programming Distributor environments — pay-TV, OTT bundles, and addressable cable. A complex measurement layer we are actively refining.
📺
Reach & Frequency

Impressions delivered, household penetration, frequency curve.

MVPD
🎯
Audience Targeting

Addressable segments, lookalike modelling, and overlap analysis.

Addressable
📈
Lift / Incrementality

Brand and sales lift attributable to MVPD spend.

Measurement
💸
Cost Efficiency

CPP, CPM, and effective CPA against household-level outcomes.

Efficiency
In Development
Detailed methodology + case study coming soon

MVPD 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.

Ask Your Data Questions in Plain English

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.

🔒 dashboard.onebigtable.us / ask
OBT AI
CEO
How many safety violations were there in May?
Querying semantic layer…
Safety violations by month — 2026
May: 47 violations — 18% below Q1 average, lowest in 8 months. Trend is down thanks to new HOS training.

Book a Discovery Call.
Let's See What Your Data Can Become.

60 minutes. No obligation. A written summary is yours to keep.

Book a Discovery Call