Data Platforms & Modernisation

Move from on-prem or VM SQL to an Azure lakehouse — incrementally and safely. We stand up landing zones, metadata-driven ingestion, medallion layers, and a semantic model ready for BI.

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Who it’s for

SMEs running SQL Server, SSIS/SSAS/SSRS and Power BI on-prem or in VMs who want a staged move to Azure without a risky big-bang rewrite.

Outcomes

Landing zones, networking, and cost controls in place.
Metadata-driven ingestion for files/APIs/DBs with schema-drift handling.
Medallion (Bronze/Silver/Gold) layers with Delta/Parquet and partitioning.
Semantic model ready for trusted Power BI reporting.
Operable pipelines: logging, retries, observability and runbooks.

What you get

Architecture & migration plan; environments via IaC (Bicep/ARM/Terraform).
Azure Data Factory/Databricks pipelines; Functions/Logic Apps where appropriate.
Patterns: CDC, incremental loads, schema registry, compaction & retention.
Promotion flows (Dev/Test/Prod) and CI/CD ready for data.
Handover: runbooks, backlog, and an operations dashboard.

Packages

Readiness Sprint (2–3 weeks)

Discovery, sizing, landing-zone & governance design, roadmap.

Pilot Slice (4–6 weeks)

1–2 sources to Bronze→Silver→Gold, initial semantic model, BI connection.

Scale-out (ongoing)

Source onboarding, performance tuning, cost optimisation, governance gates.

Tech we use

Microsoft & Azure: SQL Server, Azure SQL/Managed Instance, Synapse SQL, SSIS/SSAS/SSRS, Power BI, Power Apps/Power Platform, Azure Data Factory, Databricks, Azure Storage, Delta/Parquet, Logic Apps, Function Apps, Event-driven patterns. Languages: T-SQL, Python, Spark/SQL. Infra: Virtualisation/VMs, IaC, CI/CD.

Note: You may reference Microsoft product names and icons consistent with Microsoft brand guidelines. Avoid using trademarked logos unless permitted; partner badges are preferred.

FAQs

How “incremental” is incremental?

We migrate per subject area or per pipeline. You get value in weeks, not months, and we retire legacy pieces as we go.

Do we need Databricks or can we stay SQL-first?

We’re pragmatic. We often start SQL-first and introduce Spark where data volume or transformations demand it.

Will our Power BI estate still work?

Yes. We stabilise and progressively move models to a governed semantic layer so reports become faster and more reliable.

Ready to modernise without the chaos?