Migrate, scale, and govern at enterprise scale - without freezing the business.
Enterprise data warehouse projects don't fail because the technology is bad. They fail because nobody owned the orchestration of business, engineering, compliance, and finance. Logiciel runs the entire EDW lifecycle - from architecture to migration to managed operations - for US enterprises that can't afford a 24-month freeze.
Symptoms of EDW sprawl most enterprise teams underestimate:
Most enterprises here are dealing with:
Enterprise EDW without enterprise paralysis.
Migration playbook - proven path from Teradata, Netezza, Oracle to Snowflake, Databricks, BigQuery. Migration playbooks proven across Teradata, Netezza, Oracle, and on-prem Hadoop migrations encode 30+ engagements of pattern recognition, not first-rodeo risk.
Parity testing automation - prove every report, every cent, every metric matches before cutover. Parity testing automation eliminates the manual reconciliation work that historically cost migration programs months of delay.
Phased decommission - keep legacy systems live until parity is signed off; no all-or-nothing risk. Phased decommission with parallel running means migration risk is structurally bounded; you don't bet the business on a single cutover weekend.
US-aligned program management - your stakeholders meet the same project lead every week. US-aligned program management means stakeholders meet the same lead every week, eliminating the staffing turnover that breaks trust on long programs.
Trading data, risk models, regulatory reporting — sub-second SLAs and audit-ready governance.
Listing data, transaction pipelines, geospatial analytics — multi-source consolidation.
EHR integration, claims pipelines, clinical analytics — HIPAA-aware infrastructure.
Product analytics, customer 360, usage-based billing — embedded and operational data.
Inventory, pricing, order, and customer pipelines — real-time and high-throughput.
IoT, project, and supply-chain data — operational analytics on hybrid stacks.
| Dedicated Pod | Staff Augmentation | Project-Based Delivery |
|---|---|---|
| Embedded data engineering pod aligned to your sprint cadence — typically 3–6 engineers + a US lead. | Senior data engineers, architects, and SMEs slotted into your team to unblock specific work. | Fixed-scope, milestone-driven engagements with clear deliverables and outcomes. |
We map your stack, workloads, team, and constraints in a working session - not an RFP response.
Reference architecture grounded in your reality, with capacity, cost, and migration plans.
Iterative implementation with weekly demos, code reviews, and your team in the loop.
Managed operations or knowledge transfer - your choice. Both with US-aligned coverage.
Continuous tuning of cost, performance, and reliability against measurable SLAs.
Multi-year EDW architecture aligned to business outcomes.
Automated reconciliation across thousands of reports and metrics.
SOC 2, HIPAA, SOX, GDPR, state privacy frameworks built-in.
Teradata, Netezza, Oracle, SQL Server, on-prem Hadoop to cloud.
Query, storage, and workload optimization for Snowflake/Databricks/Redshift.
24/7 EDW operations with US-aligned escalation paths.
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.
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.
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.
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.
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.
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.
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.
Logiciel will run a 4-week EDW assessment of your current footprint. Output: a costed, phased modernization plan defensible to your CFO and your board.
