Cross-team data incidents vanished once every domain owned its product with dbt tests and CI gates…. Director of Data Engineering Fortune 500 Grocer Campaign lists that took two weeks now spin up in two hours. Marketing finally moves at market speed…. Head of CRM European Retailer During the chip shortage we reprioritized SKUs in days, not weeks. The platform paid for itself…. CEO Global Manufacturing Group What Is a Modern Data Platform? A modern data platform is your company’s single, trusted foundation for every metric, report, and AI model. Instead of juggling dozens of siloed tools, you get one governed, scalable environment built for both today’s reporting and tomorrow’s innovations.Not Ready to Talk?Get Our Free Guidefor More In-Depth InsightsModernizing the Core: Data Platform Architecture & AI Readiness Technical roadmap to build an AI-ready lakehouse-plus-mesh core, complete with governance and FinOps checklists. Why Smart Businesses Love ItOne version of the truth – Finance, Ops, and Marketing finally see the same numbers.Instant Insights – Answers arrive in minutes, not days of spreadsheet cleanup.AI-ready from day one – Clean, well-governed data feeds models that actually reach production.Costs stay lean – Retire legacy licenses and pay only for the storage and compute you use.Compliance built in – Automated lineage and role-based access keep auditors (and customers) happy.In short: it’s the fastest way to shift from reactive reporting to proactive, data-driven growth. We deliver this through modern data architecture consulting services paired with data integration consulting, so the platform fits your business, not the other way around. Want to see how close you already are? Our senior experts will assess performance gaps, governance risks, and underused features, then develop a roadmap that delivers business value in weeks, not months. Get a complimentary consultation with one of our Senior experts to discover how we can transform your business.Get Your AssessmentOur 5-Step Data Platform Modernization PathAssessment and StrategyAssess current state, define business-aligned goals, and create a strategic roadmap with executive backing.12Architecture Design and Tool SelectionDesign the future architecture, select core tools, and plan implementation with governance in mind.3Pilot and Quick WinsRun small pilots to validate the stack, gather feedback, and show early value.Core Platform Build-OutScale pipelines, integrate BI, apply governance, and migrate core workloads.45Enrichment and AI EnablementDeploy ML, optimize usage, and unlock new value through data products and AI.Once the platform is up and running, a continuous FinOps + DataOps loop keeps costs lean, quality high, and new use-cases flowing. In other words, the three steps light the fuse; the optimization cycle delivers the compounding ROI.What Our Data Platform Modernization Services Deliver Capability Lakehouse core Data Mesh operating model Declarative pipelines FinOps guard-rails Governance-by-design How it works Unified object storage + elastic compute Domains publish certified “data products” SQL-as-code with automated tests & lineage Auto-suspend, workload tagging, committed-use discounts Catalog, RBAC, column masking, EU AI-Act readiness Why it matters One copy of data for BI and ML 3× faster delivery of new analytics Breaks the “Excel chaos” loop 20–40 % cloud-spend reduction Compliance without slowing teamsDownload OurComplimentary Whitepaper Modern Data Platforms: A Business Case for Unified IntelligenceC-suite guide that quantifies ROI and shows how unified data slashes the $12.9 M annual cost of bad dataDownload WhitepaperProven Business Impact 5× ROI in 18 monthsPhased lakehouse rollout for a 20-country manufacturer 20 % unplanned-downtime reductionPredictive maintenance using real-time sensor streams Dashboard breakages virtually eliminatedGlobal retailer unified 100+ data engineers under a “transformation core” on Snowflake & dbtClients Across Industries Modern Data Platform in Action: From Siloed Dashboards to Real-Time DecisionsA 20 000-employee European manufacturer was living on contradictory QlikView dashboards and weekly Excel roll-ups. We began with a three-month Assess phase to map every silo; our data warehousing consultants shaped the migration path, and our data integration consulting team built the pipelines on Azure–Databricks with Power BI on top. Seven months in, plant managers were watching live production metrics and a predictive-maintenance model that flagged failures two weeks ahead. By month 18 the company had retired 150 legacy reports, cut unplanned downtime 20 %, and unlocked more than €10 million in three-year efficiency upside—all on a modern data platform that now fuels new AI and supplier-data-sharing products.Ready to find your first 90-day win? A complimentary consultation shows exactly where to start.Talk to an ExpertExplore Related ServicesWe help you clean, move, and manage your data, from setting up better systems to ensuring it’s secure, accurate, and ready for smarter decisions. View Our ServicesData Engineering & IntegrationRead More Cloud MigrationRead More Modern Data ArchitectureRead More Data Warehousing & Data LakesRead More Data GovernanceRead More Data Quality & Master Data Management Read More AI Strategy ConsultingRead More BI Platform ImplementationRead More FAQData Platform Modernization FAQsHow long until we see value?First production slice typically goes live in ~4 months; full estate in 12–18 months with incremental wins each quarter. Because our data integration engineering services run in parallel with design, your first live use cases typically land in the early months.Do we migrate everything at once?No. We start with one high-value domain, prove ROI, and iterate, minimizing change fatigue. Our data warehousing consultants plan phased cutovers so existing reporting keeps running while we modernize behind the scenes.Will cloud costs explode?FinOps controls (auto-suspend, workload scheduling, reserved-use discounts) consistently cut spend 20–40%. Our data integration consulting services include FinOps guardrails (usage policies, scheduling, and right-sizing) to prevent surprise bills.How do you protect sensitive data?Role-based access, column masking, and automated lineage meet GDPR and upcoming EU AI-Act standards from day one. What resources do we need internally?An exec sponsor plus 3–5 subject-matter SMEs for workshops; B EYE handles the heavy lifting. You’ll have a dedicated modern data architecture consultant working alongside your sponsor and SMEs, supported by our engineers.