Dimensional and relational modeling, schema design, and seamless data migrations with minimal downtime and maximum integrity — powered by AI-assisted mapping and Microsoft's unified data platform.
Start a ProjectFrom legacy database modernization to cloud-native data architectures — every engagement is designed for performance, scalability, and long-term maintainability.
Design fact and dimension tables optimized for analytical queries, Power BI, and SSAS tabular models — following Kimball methodology for maximum performance and usability.
Normalized relational schemas with proper primary/foreign key relationships, constraints, and indexing strategies — built for transactional integrity and long-term maintainability.
Analyze source systems to understand data structures, volumes, quality, and relationships before migration begins — eliminating surprises mid-project.
Migrate databases across versions, platforms, or cloud environments — SQL Server on-prem to Azure SQL, Synapse, or Fabric — with minimal downtime and zero data loss.
Implement row-level security, column-level encryption, and role-based access control within the data model — aligned to regulatory and compliance requirements.
Index tuning, partitioning strategies, columnstore indexes, and query optimization for high-performance data access at enterprise scale.
Every engagement incorporates Microsoft's AI layer — reducing risk, accelerating timelines, and improving data quality throughout the migration lifecycle.
AI-powered assessment of on-premises workloads with automated readiness reports, compatibility analysis, and cloud sizing recommendations.
Unified analytics platform combining data lake flexibility with data warehouse structure — the modern foundation for AI-ready data architectures.
Machine learning-assisted source-to-target schema matching that identifies relationships and suggests field mappings automatically — reducing manual effort by up to 70%.
Natural language assistance for writing T-SQL, designing schemas, and troubleshooting migration issues — accelerating development and reducing errors in real time.
See how AI-enhanced Data Modeling & Migration delivers measurable results across industries.
An insurance company migrated a critical SQL Server 2008 policy database to Azure SQL with zero data loss and under 2 hours of downtime — guided by Azure Migrate AI.
A retailer's Power BI reports went from 45-second load times to under 3 seconds after a Kimball star schema replaced a complex OLTP model.
A university unified 16 source systems — including 14 Access databases — into a single SQL Server data model in 90 days using AI-assisted schema mapping.
A logistics company cut nightly batch processing from 8 hours to 45 minutes by migrating analytical workloads to Azure Synapse with a redesigned columnar model.