Microsoft Fabric Consulting: Lakehouse Architecture to Production Analytics
Fabric promises to unify your entire data stack. The reality is that getting there requires architects who understand OneLake design, lakehouse medallion patterns, Direct Lake optimization, and the migration path from your current Azure services. That expertise is scarce — Fabric architect demand is up 180% year over year.
Lakehouse Architecture
OneLake, medallion pattern, Delta tables, lakehouse vs warehouse design
Direct Lake Analytics
Power BI reading directly from OneLake — no import, no refresh delay
Data Pipeline Engineering
Fabric pipelines, Dataflows Gen2, notebooks, and orchestration
Real-Time Intelligence
Eventstreams, KQL databases, and real-time dashboards in Fabric
Everyone wants Fabric. Almost nobody has done it in production.
Microsoft Fabric launched as GA in late 2023. In less than two years, it has become the default data platform strategy for Microsoft-committed enterprises. The problem: the talent pool hasn't caught up with the demand.
Fabric architects need a specific combination of skills: deep understanding of lakehouse patterns (medallion architecture, Delta tables, partitioning), experience with the Fabric-specific services (OneLake, Direct Lake, Dataflows Gen2, Eventstreams), and the ability to design migration paths from legacy Azure services (Synapse, ADF, ADLS). Finding engineers with production Fabric experience — not just certification — is the bottleneck.
Xylity's network has been actively sourcing and evaluating Fabric specialists since the platform's public preview. Through consulting-led matching, we verify hands-on production experience through scenario-based assessments: lakehouse design reviews, Direct Lake optimization challenges, and pipeline architecture walkthroughs.
Microsoft Fabric consulting capabilities
Every Fabric engagement below is staffed by pre-qualified architects and engineers with verified production experience — matched to your specific migration path and data environment.
Lakehouse Architecture & Design
OneLake structure, workspace strategy, medallion layer design (bronze/silver/gold), Delta table optimization, partition strategy, and governance framework. The foundation that everything else — from pipelines to Direct Lake reports — depends on.
Direct Lake Implementation
Power BI semantic models reading directly from OneLake Parquet files. No import, no scheduled refresh, near-real-time analytics at lakehouse scale. Optimization for query performance, V-Order, and table partitioning that makes Direct Lake viable at enterprise data volumes.
See Power BI consulting →Data Pipeline Engineering
Fabric data pipelines, Dataflows Gen2, Spark notebooks, and scheduled orchestration. Ingesting from 50+ source systems, transforming through medallion layers, and loading into lakehouse and warehouse endpoints. Production-grade error handling, logging, and alerting.
Real-Time Intelligence
Eventstreams for streaming data ingestion, KQL databases for real-time querying, and real-time dashboards that reflect the latest data without batch delay. IoT telemetry, financial transactions, and operational monitoring use cases.
Migration from Azure Synapse
Dedicated SQL pool to Fabric warehouse. Synapse pipelines to Fabric pipelines. ADLS Gen2 to OneLake. Mapping the migration path, executing it with minimal downtime, and validating data integrity post-migration. The most common Fabric engagement.
See data warehousing →Fabric + AI Integration
Using the Fabric lakehouse as the data foundation for AI workloads: feature engineering from Delta tables, ML model training on Fabric Spark clusters, and AI applications that read from OneLake. The data + AI convergence point.
The unified platform — every workload, one experience
Data Engineering
Spark notebooks, lakehouse tables, Delta format, medallion architecture
Data Factory
Pipelines, Dataflows Gen2, 150+ connectors, orchestration, monitoring
Data Warehouse
T-SQL endpoint, cross-database queries, Direct Lake integration
Power BI
Direct Lake, semantic models, paginated reports, embedded analytics
Real-Time Intelligence
Eventstreams, KQL databases, real-time dashboards, Reflex triggers
Data Science
ML experiments, model registry, Spark MLlib, AutoML integration
OneLake
Unified storage, shortcuts, data sharing, governance, lineage
Purview Integration
Data catalog, sensitivity labels, access policies, compliance
Fabric, Databricks, or both?
Platform selection is one of the most consequential data architecture decisions. Xylity consults on this decision and provides pre-qualified specialists for both platforms.
Choose Fabric when...
Microsoft commitment: Your org runs M365, Azure, Power BI, Dynamics 365
Unified simplicity: You want one platform for DE, warehousing, BI, and data science
Direct Lake: Power BI at lakehouse scale without import/refresh is a priority
SaaS preference: You want Microsoft managing the infrastructure
Choose Databricks when...
Multi-cloud: You run on AWS, GCP, or a hybrid cloud strategy
Open-source first: You value open table formats (Delta, Iceberg) and Spark ecosystem
ML-heavy: Data science and MLOps are primary workloads, not just BI
Unity Catalog: Cross-platform governance is a requirement
See Databricks consulting →Pre-qualified Fabric architects, matched to your migration path
Architecture Discovery
We map your current data stack, migration targets, and Fabric adoption goals. Whether you're greenfield or migrating from Synapse — the matching starts from your architecture.
Fabric-Specific Matching
Architects matched for your specific Fabric workloads: lakehouse design, Direct Lake, data pipelines, or real-time intelligence. Production experience verified through scenario assessment.
Technical Evaluation
Candidates walk through Fabric-specific scenarios: OneLake design decisions, medallion layer trade-offs, Direct Lake optimization strategies. 92% pass your technical screen on first match.
Deploy & Deliver
Your Fabric specialist contributes from week one. A delivery manager provides continuity through the migration and scales the team as workloads expand.
Fabric talent for enterprises and IT services companies
Adopting Fabric but can't find architects with production experience?
Fabric adoption is accelerating faster than the talent market can keep up. Whether you're designing a greenfield lakehouse, migrating from Synapse, or implementing Direct Lake for Power BI — Xylity matches pre-qualified Fabric architects who've done it in production. Companies of 500-10,000 employees trust our consulting-led process for this high-demand specialization.
Start a Consulting Engagement →Client committed to Fabric but you don't have Fabric architects?
Fabric is rapidly becoming a requirement in Microsoft-committed accounts. When your client's project calls for lakehouse architects and Direct Lake specialists your bench doesn't have, Xylity's network delivers curated profiles in days. IT services companies of 20-1,000 employees use Xylity to take on Fabric engagements without building a Fabric practice from scratch.
Scale Your Fabric Delivery →Fabric consulting — answered
Your Fabric project deserves architects
who've built production lakehouses before.
Tell us about your Fabric goals. We'll match pre-qualified architects with verified production experience — in an average of 4.3 days.