Data Lakehouse Architecture
Combine the flexibility of a data lake with the structure and performance of a data warehouse. We design and implement modern data lakehouse architectures on Azure Synapse and Databricks that unify your analytical and data science workloads on a single platform.
One Platform for All Your Data Workloads
Organisations that maintain separate data lakes and data warehouses face a familiar set of problems: data duplication, inconsistent definitions, complex ETL between the two environments, and escalating infrastructure costs. The data lakehouse pattern solves this by applying warehouse-style schema enforcement, ACID transactions, and query performance to data stored in open lake formats.
skios designs data lakehouse architectures on Azure Synapse Analytics and Databricks that consolidate your structured, semi-structured, and unstructured data into a single governed platform. We implement medallion architecture (bronze, silver, gold layers), Delta Lake for reliable data management, and unified access for both BI reporting and data science workloads. The result is a platform that serves traditional warehouse queries, real-time analytics, and ML model training from the same data without duplication or inconsistency.
Data Lakehouse Capabilities
Medallion Architecture
Bronze, silver, and gold data layers providing progressive data refinement from raw ingestion to business-ready datasets.
Delta Lake Integration
ACID transactions, schema enforcement, and time travel on data lake storage for reliable, auditable data management.
Unified Analytics
Single platform serving BI dashboards, ad-hoc SQL queries, and data science notebooks without data movement or duplication.
Data Governance
Cataloguing, lineage tracking, access controls, and data quality monitoring across all lakehouse layers and workloads.