Pilot environments never reach production
Teams deliver Fabric POCs but lack the architecture and governance knowledge required to transition to production workloads at enterprise scale.
ENTERPRISE PROGRAMS — Microsoft AI Foundry Program Track — Available for Enterprise Team Delivery
Platform Enablement
Move your Fabric pilots into production with MCT-led enablement covering Lakehouse architecture, Real-Time Intelligence, Direct Lake semantic models, and DP-600/DP-700 certification preparation.
Why This Matters Now
Pilot environments never reach production
Teams deliver Fabric POCs but lack the architecture and governance knowledge required to transition to production workloads at enterprise scale.
Direct Lake adoption gap delays analytics ROI
Teams default to Import mode because Direct Lake query optimisation and capacity sizing are not covered in standard Fabric onboarding material.
Capacity governance deferred until billing surprises
Workspace proliferation and unconfigured capacity rules result in unexpected Fabric capacity charges that arrive after the pilot phase is already complete.
Strategic context: Fabric consolidates six previously separate Azure analytics services — early enablement reduces long-term licensing complexity and accelerates the path from pilot to production.
Capability Coverage
Design and implement bronze/silver/gold medallion patterns using OneLake, Lakehouse, and Warehouse for enterprise analytics workloads with Delta format throughout.
Build real-time data pipelines using Eventstream, KQL databases, and Real-Time dashboards for operational analytics and event-driven monitoring at enterprise scale.
Implement Direct Lake connectivity for high-performance semantic models that eliminate Import mode refresh bottlenecks and reduce storage duplication across the organisation.
Configure workspace governance, sensitivity labels, data lineage documentation, and compliance controls using Purview integration for regulated data environments.
Design orchestrated data movement using Data Factory pipelines, Dataflows Gen2, and Data Activator for automated alerting and reactive data pipeline management.
Structured exam preparation for Fabric Analytics Engineer (DP-600) and Fabric Data Engineer Associate (DP-700) with hands-on lab coverage of production scenarios.
Delivery Approach
Assess
Map existing data platform components, identify migration readiness, and assess team skill gaps across data engineer, analytics engineer, and BI developer roles.
Design
Design parallel learning tracks for data engineering (Lakehouse, pipelines, DP-700), analytics engineering (semantic models, DP-600), and BI development (Power BI + Direct Lake).
Enable
Deliver hands-on Fabric labs, Purview configuration workshops, and certification preparation using real workspace environments with production-representative data.
Adopt
Close with workspace naming standards, capacity governance rules, deployment pipeline templates, and team-specific runbooks for sustained Fabric platform operation.
Capability Programs
Proof & Perspectives
Data teams were moving from legacy reporting platforms to Azure-centric analytics environments, with uneven readiness across architecture, engineering, and reporting roles.
Microsoft Fabric unifies lakehouses, data warehouses, real-time intelligence, and Power BI into a single SaaS platform. Yet many enterprise teams struggle to move from an approved pilot to production workloads. This post unpacks the patterns we see in teams that succeed — and the organisational friction that trips up the rest.
Ready to Begin
Work with our team to design an enablement program matched to your team's readiness, platform priorities, and delivery timeline.
Engagement Confidence
A direct, founder-led review before scope, delivery model, and commercial terms are proposed.
Response window
< 1 business day
Client coverage
India + global teams
Engagement format
Virtual, on-site, hybrid