One governed place for every source: ERP, CRM, web, IoT, spreadsheets. Built so analysts trust the numbers and AI can use them.
Lakehouse architecture on Azure, AWS, Google Cloud or Databricks
Ingestion from SAP, Oracle, NetSuite, Salesforce, files and APIs
Medallion (bronze / silver / gold) modeling with data-quality tests
Cost controls, lineage, cataloging and role-based access
Migration off legacy warehouses with parallel-run reconciliation
A data lake stores raw data cheaply in open formats. A lakehouse adds table-level structure, transactions and governance on top, so the same store serves BI dashboards, data science and AI without copying data between systems.
A scoped pilot that lands two or three priority sources and one business-ready data model typically takes 6 to 10 weeks. Scope is agreed in writing before work starts.
Microsoft Azure and Fabric, Amazon Web Services, Google Cloud and Databricks. We recommend based on where your data and skills already live.
A 45-minute working session, no slides.