Every UAE enterprise data leader we work with has a project artefact from a previous data platform initiative. Sometimes it's a strategy deck. Sometimes it's a reference architecture diagram spanning three walls. Sometimes it's a governance framework nobody has read. What's rarely present is a pipeline running in production, a catalog anyone consults, or a business report the sponsor trusts enough to make a decision from.
The instinct is to scope more ambitiously — a full warehouse migration, a company-wide governance programme, an enterprise-scale data mesh. The instinct produces the same artefact set as last time. What produces trusted data is finishing one domain end-to-end — pipelines that run, quality that's measured, remediation that closes, catalog that's used — and then scaling from that evidence rather than from a slide. B4 is the sprint that finishes the first one.
Six streams,
ending in one domain trusted.
Platform setup and domain scoping front-load weeks 1–3. Pipeline build, catalog, and quality overlap through weeks 3–8. Remediation workflow and handover close weeks 8–10.
Platform setup
Platform MVP provisioned on the selected stack. Environments, access controls, and cost tagging wired from day one — not retro-fitted later.
Domain scoping
One business domain agreed with a named business sponsor. Pipeline surface, source systems, and SLA committed in writing. No moving targets after week two.
Pipeline build
Domain pipelines built end-to-end — ingestion, transformation, delivery. Schema contracts explicit. Backfill and reprocessing strategies designed, not improvised.
Catalog & governance hooks
Domain assets catalogued with ownership, lineage, and access classification. Governance hooks wired to your identity provider and approval workflow.
Quality dashboards
Freshness, completeness, and defect metrics on named assets. Alert thresholds tuned against real pipeline behaviour, not vendor defaults.
Remediation workflow & handover
Alert-to-owner routing, runbooks per alert class, escalation to freshness SLA. Data team trained. 30/60/90-day check-ins scheduled.
Ten weeks maximum.
Six minimum. Four phases.
Phase count is fixed. Duration flexes with source-system integration complexity, platform selection lead-time, and the number of upstream systems required for the target domain. Milestones are signed gates — not aspirations.
Platforms scored,
not on keynote demos.
Every engagement runs a six-criteria scorecard in weeks 1–2. Each candidate platform stack scored 1–5 against evidence from your estate and your team's operator profile. Signed by the data lead before Phase 2 begins.
From reports reconciled by hand
to one trusted domain.
A typical pre-engagement state has source systems in silos, exports moved by CSV or manual query, and a business team reconciling numbers before every report. The engagement stands up the trusted layer between source systems and consumers.
Reference pattern. Some engagements ship two related domains in the sprint window if they share source systems and are already well-scoped. The discipline is finishing what starts — never leaving a domain half-built to add scope.
A national retailer,
sales domain trusted.
Representative pattern for a UAE national retailer of this scale — multi-format operator, no unified data platform, sales reporting reconciled manually across siloed systems. Ranges reflect target outcomes NexITC underwrites in scope for this class of engagement. N=1 — illustrative composite, not a specific client.
Five artifacts,
each with signed acceptance.
Every deliverable has documented acceptance criteria signed at engagement kickoff. Nothing more, nothing less.
Platform MVP
Selected stack provisioned with environments, access controls, and cost tagging wired from day one. The base every domain runs on.
Domain Pipelines
One domain end-to-end — ingestion, transformation, delivery — with explicit schema contracts and backfill patterns.
Catalog Entries
Domain assets catalogued with ownership, lineage, and access classification. Not a separate spreadsheet.
Quality Dashboards
Freshness, completeness, and defect metrics on named assets. Thresholds tuned against real pipeline behaviour.
Remediation Workflow
Alert-to-owner routing, runbook per alert class, and escalation path when the fix takes longer than the freshness SLA allows — the workflow that turns a quality dashboard from a wall of red squares nobody triages into a signal your data team actually acts on.
Six outcome metrics,
measured pre and post.
Success is not "the platform is live." It is measured against six specific outcomes captured in a baseline report at engagement start and re-measured at post-handover steady state.
Honest scoping.
B4 is a fit when specific conditions are met. It is not a fit when other conditions are. We say so before the scope conversation, not after the commercial commitment.
Someone with the standing to commit the domain scope, sign the freshness SLA, and defend the platform investment. Without that seat filled, scope moves in week five.
Sales, finance, supply chain, customer — one domain the sponsor cares about and whose source systems are accessible. If "which domain" isn't obvious, sequence [[A6|A6 Data Trust Sprint™]] first.
The application teams that own the source systems have to release read access and commit to responsive support for schema questions. Access delays are the most common cause of Phase 2 slippage.
Signs off platform selection, pipeline design, and quality thresholds. Typically 30% time commitment through the engagement.
Who will actually use the trusted domain — analytics team, business report writers, AI/ML use cases. Otherwise the platform delivers with no first customer.
That's a multi-year programme, not a sprint. B4 delivers one domain and the pattern for the rest. Full-estate scope produces a strategy deck, not shipped domains.
Those sit on top of the trusted domain layer B4 delivers, built by your analytics team or BI partner. Merging platform and BI in one engagement produces worse outcomes.
That's C4 DataOpsCommand™ — sensible as the next engagement after B4, or immediately if a platform is already in place.
Start with A6 Data Trust Sprint™ — 3-week readiness assessment to pick the first domain and confirm sponsorship.
Fixed fee.
Milestone-based.
Total engagement fee agreed in the scope statement. Not time-and-materials. Not day rate. Every engagement is preceded by a scope conversation to ensure fit before commitment.
Five, most asked.
Q_01Why one domain instead of the full data estate?
Because every full-estate data platform we've ever seen scoped delivers on time in year three, produces a governance framework nobody adopts, and gets rebuilt by the next CDO within eighteen months.
One domain delivered end-to-end proves the pattern in eight weeks, generates real business value the sponsor can defend, and produces the exact reference implementation that lets domains two through ten roll out on the same rails.
The scope discipline is not a limitation — it is the strategy.
Q_02Which platform stack do you recommend?
Q_03Do you build the reports and dashboards on top?
Q_04What is a "remediation workflow" and why is it in scope?
Q_05What comes after the sprint?
One name
on the engagement letter.
A named Practice Lead is accountable for delivery, commercial outcomes, and the client relationship throughout the engagement. Not a project manager who disappears after kickoff. Not a partner who nods at the SOW and vanishes.
Practice Lead — Cloud/Edge
Present at every phase gate, every scope decision, every difficult conversation. Available for 30/60/90-day post-handover check-ins as part of the engagement.
Including scope amendments.
Signs off all 5 deliverables.
With executive sponsor.
Authorised to negotiate.
CEO within 24 hours.
30/60/90-day check-ins.
Prior. Peer. Next.
Data Trust Sprint™
3-week data readiness assessment that surfaces which domain to sprint first and what platform selection criteria matter for your estate. Sensible if the domain choice isn't yet obvious.
Unified Observability + AIOps Build™
Peer Cloud/Edge build focused on service health and MTTR reduction. Often sequenced or paired — B4 delivers the trusted data foundation, B6 delivers the operational telemetry that runs on top of and around it.
DataOpsCommand™
Managed data platform operations. Runs the pipelines, monitors quality, executes the remediation workflow, and evolves the platform as domains two and beyond come online.
Thirty minutes.
No slide deck.
A structured 30-minute scope conversation with the Practice Lead. You describe the current data estate, the first domain, and the organisational pressure. We describe whether B4 is the right engagement — and if not, what is.