Data & AI
Bring your data into one governed estate on Microsoft Fabric, then put AI to work on it: assistants, agents and forecasts your teams can trust.
Why Data & AI matters
Most organizations already have the data they need. It sits in ERP, core banking, CRM and file shares, copied into reports that disagree with each other, so every new dashboard or AI idea starts with another extraction project.
We design the data landing zone first: one lake, clear domains, governance in Microsoft Purview, and a semantic model the business agrees on. Analytics and AI are then built on that foundation instead of beside it.
14 offerings in 4 areas
Pick an area. Every offering can be scoped on its own or combined into a program.
Fabric data landing zone
Workspaces, domains, capacities and Git-backed deployment set up as a governed foundation.
Ask about thisDatabase mirroring
Near real-time replicas of Oracle, SQL Server, Snowflake and other sources in OneLake, without building pipelines.
Ask about thisLakehouse & warehouse
Medallion-layered lakehouses and warehouses for data engineering and SQL analytics.
Ask about thisMigration from legacy BI
Move Synapse, SSIS, SSAS and on-premises warehouses onto Fabric in planned waves.
Ask about thisPower BI & semantic models
Certified semantic models and Direct Lake reports that everyone reads the same way.
Ask about thisReal-Time Intelligence
Eventstreams and KQL databases for operational data that cannot wait for a nightly load.
Ask about thisExecutive dashboards
A small set of trusted measures for leadership, with drill-through to the detail.
Ask about thisGrounded assistants (RAG)
Assistants that answer from your documents and data, with citations, built on Azure AI Search and Azure OpenAI.
Ask about thisAgents & automation
Agents in Microsoft Foundry and Copilot Studio that complete multi-step work under human review.
Ask about thisDocument intelligence
Extract fields from forms, invoices and contracts into structured data.
Ask about thisForecasting & ML
Demand, risk and capacity forecasts with Azure Machine Learning and Fabric data science.
Ask about thisMicrosoft Purview
Catalog, lineage, sensitivity labels and data loss prevention across the estate.
Ask about thisResponsible AI
Evaluation, content safety and access controls in place before an AI workload goes live.
Ask about thisData & AI in practice
Client stories and solution blueprints that use this practice’s technology.
Recognized by Microsoft for Data & AI
Designations and specializations are awarded by Microsoft against certified people, delivered projects and customer outcomes.
Start from something that already works
Fabric Data Landing Zone
A governed data foundation, ready in weeks
- Mirrors Oracle, SQL Server and MongoDB into OneLake
- Medallion lakehouse, Direct Lake Power BI, Data Agent
- Deployed as code with Azure DevOps and Fabric Git
An architect will walk through it against your environment.
Book a walkthroughRead before you decide
Microsoft Fabric vs the traditional data warehouse: what actually changes
How Microsoft Fabric's architecture differs from a classic data warehouse, from one copy in OneLake and shortcuts to Direct Lake and capacity, and what stays the same.
Mirroring Oracle into Microsoft Fabric without building ETL
How Microsoft Fabric mirrors Oracle databases using LogMiner and the on-premises data gateway, what lands in OneLake, what it costs, and where GoldenGate still fits.
Building a Fabric data landing zone: medallion, governance and Direct Lake
A practical blueprint for a Microsoft Fabric data landing zone, covering workspaces, bronze, silver and gold layers, mirroring, Purview, Direct Lake and Git-based CI/CD.
Five ways to engage
Evidence-led findings and a prioritized remediation plan.
Microsoft-funded workshops: CAF, security, AI readiness, modernization.
Validate against success criteria before scaling investment.
Architecture, build, migration, testing, training and handover.
24×7 monitoring, SOC, FinOps and continuous improvement.
Eligible engagements can be funded by Microsoft
We nominate eligible work for Microsoft investment, lowering your cost and de-risking adoption.
Microsoft co-invests in eligible delivery work.
Credits toward consumption during pilots and migration.
Access to Microsoft engineers on eligible projects.
Start your Data & AI conversation
A short discovery workshop with an architect from this practice, ending in a written recommendation.