Azure Data Platform & SQL Server Tuning
Azure Data Factory, Synapse Analytics, Microsoft Fabric and Azure SQL delivered by Microsoft certified data engineers.
A Microsoft Data Estate That Holds Together
Azure gives you many ways to build the same pipeline. The difference between a platform that scales and one that becomes a maintenance burden is usually the choices made in the first few weeks. We make those choices explicitly and document why.
Our team holds the Microsoft Certified Fabric Data Engineer Associate, Azure Data Engineer Associate and Azure Data Fundamentals credentials. We work across the full estate from ingestion through to the Power BI semantic model that the business actually reads.
What We Do On Azure
Azure Data Factory
Metadata-driven ingestion and orchestration rather than hand-built copy activities.
- Metadata-driven pipeline frameworks
- Self-hosted and Azure integration runtimes
- Incremental and CDC ingestion
- Retry, alerting and monitoring
Synapse Analytics
Dedicated and serverless SQL, plus Spark pools where they earn their place.
- Dedicated SQL pool design
- Serverless SQL over the data lake
- Synapse Spark workloads
- Workload management and classification
Microsoft Fabric
OneLake, lakehouses and Direct Lake semantic models on the Fabric platform.
- OneLake and lakehouse design
- Fabric pipelines and dataflows
- Direct Lake semantic models
- Capacity sizing and monitoring
Azure SQL & SQL Server Tuning
Operational databases tuned for the transactions they carry.
- Azure SQL Database and Managed Instance
- Deadlock analysis and stored procedure tuning
- Index and execution plan review
- High availability and failover
- Migration from on-premises SQL Server
Power BI Reporting
Semantic models and reports built on a governed foundation.
- Star schema semantic models
- DAX optimization
- Row level security
- Refresh and gateway strategy
Security and Governance
Identity, network and data protection aligned to enterprise policy.
- Entra ID and managed identities
- Private endpoints and network isolation
- Purview cataloguing and lineage
- Key Vault secret management
What You Get
- A documented Azure data architecture with the trade-offs written down
- Metadata-driven pipelines that scale without new code per source
- Synapse or Fabric workloads sized against real query patterns
- Power BI models built on a governed semantic layer
- Security aligned to Entra ID, private networking and Key Vault
- Infrastructure as code and CI/CD for every environment
AI & GenAI on Azure
Azure OpenAI is straightforward to switch on and easy to deploy badly. We build the surrounding data engineering: retrieval over your own governed content, private networking so nothing traverses the public internet and Entra ID identity carried through from the user to the document they are allowed to see.
- Azure OpenAI deployments with content filtering and quotas
- Azure AI Search with vector and hybrid retrieval
- pgvector on Azure Database for PostgreSQL
- Private endpoints and Key Vault managed secrets
- Entra ID identity passed through to document level access
- Token usage tracking and cost attribution per workload
Ready to Get Started?
Book a free consultation and we will map out the right approach for your platform, your timeline and your budget.
Get Free Consultation Contact Us