Enterprise Data Warehouse Solutions That Modernize Without Disruption.

12-18 months for a Fortune 500 EDW migration, including parity validation and phased cutover. Smaller enterprise migrations (mid-market, single warehouse) run 6-9 months. The timeline breakdown: months 1-3 architecture and inventory (every report, every metric, every consumer cataloged), months 4-9 build and parallel run (target environment fully populated, every report regenerated and reconciled), months 10-15 parity validation and stakeholder sign-off (each BU signs off independently), months 16-18 legacy decommission. We never force a hard cutover — legacy stays live until parity is signed by every dependent stakeholder, eliminating the 'forgotten consumer breaks at month 13' failure mode.

Yes - change management is core to our delivery model, not an afterthought. EDW migrations fail more often from organizational misalignment than from technical issues. We embed a US-based change lead in every enterprise engagement: stakeholder alignment cadence, training plans (analyst, BI developer, data steward, executive), adoption metrics tracked weekly, and a sign-off framework that gives every dependent BU a documented voice. Most enterprise migrations involve 50-200 stakeholders across IT, business, finance, and audit; we structure the program so no stakeholder is forgotten and no executive is surprised. References available under NDA from Fortune 500 engagements.

Phased, with parallel running for 90-180 days minimum. Legacy stays live until every cutover criterion is signed off by named stakeholders. Specifically: every report is regenerated on the target and reconciled cent-for-cent with the legacy; every consumer (BI dashboard, downstream pipeline, exec report) is tested against the new source; performance is benchmarked against legacy SLAs; rollback procedures are documented and rehearsed. Zero forced cutovers — if parity isn't met, we don't cut. This adds cost and time to the migration but eliminates the 2am migration failure mode that kills careers and re-platforms. It's how we keep references.

Fixed-fee for migration milestones (architecture, environment build, each BU cutover), T&M or fixed-monthly for managed operations after cutover. Fixed-fee migration ranges from $1.5M to $8M for Fortune 500 scope, depending on legacy complexity, number of BUs, regulatory load, and target architecture. Managed operations runs $40-200K monthly depending on coverage tier (8x5 vs 24/7), pipeline volume, and US-citizen-only staffing requirements. Pricing is published transparently; we benchmark against equivalent SI pricing (Accenture, Deloitte, Wipro) at evaluation. Fixed-fee structure aligns incentives - we deliver to milestone, not to hours.

Yes - active engagements in financial services (large US banks, regional FIs, insurance carriers), healthcare (top-10 US health systems, mid-tier payers, PBM), and PropTech (institutional REITs, multi-family operators). All references are under NDA and provided during late-stage evaluation, not on first call - partly as customer protection, partly because reference quality matters more than reference quantity. We can provide 3-5 closely-matched references (industry, scale, regulatory profile) before contract signing. For US Federal customers, we maintain a separate cleared-engineer pool and can provide GovCloud references on request.

Often yes - we've co-delivered EDW programs with Accenture, Deloitte, Wipro, TCS, and Infosys, plus mid-tier US firms (Slalom, West Monroe, Booz Allen). Common shapes: SI owns business analysis and change management while Logiciel owns data engineering and platform operations; or SI handles broad transformation and Logiciel runs the EDW workstream as a sub-program. We sign mutual reference agreements and protocols up front to avoid the typical 'two vendors fighting' antipattern. About 30% of our enterprise engagements involve at least one other delivery partner - and we have explicit playbooks for co-delivery hygiene.

Multi-region architecture is a core design pattern - including air-gapped and sovereign cloud deployments (AWS GovCloud, Azure Government, Google for Government, China-specific clouds when relevant). Region-specific deployments respect GDPR, US state privacy laws, APAC regional rules, EU AI Act for AI-adjacent workloads, and FedRAMP for Federal customers. The Logiciel control plane can be regionalized so even metadata stays in-region. For pharma and life sciences customers crossing US/EU/APAC borders, we configure the data plane to enforce 21 CFR Part 11 and Annex 11 controls automatically. References across all major sovereign clouds.