Microsoft Fabric

Comprehensive data engineering solutions tailored for Microsoft Dynamics 365 and enterprise systems

MICROSOFT FABRIC

Our Fabric services

Microsoft Fabric is an all-in-one analytics platform that unifies data storage, integration, and analysis across Power BI, Synapse, and Data Factory.

Enterprise system integration via SHIR

Seamless connectivity between enterprise systems and Microsoft Fabric using Self-hosted Integration Runtime

  • SHIR setup and configuration for enterprise connectivity
  • SAP ECC 6.0, S/4HANA, and SAP BW integration
  • Oracle EBS, PeopleSoft, and JD Edwards connectivity
  • Salesforce, Dynamics 365, and ServiceNow integration
  • Microsoft Dynamics 365 F&O integration and optimization
  • Legacy mainframe and AS/400 system connectivity
  • Real-time and batch data extraction patterns
  • Delta change capture and incremental loading
  • Data streaming and real-time event processing
  • Cross-platform security model integration
  • Performance optimization for large enterprise datasets
Key deliverables
  • SHIR configuration
  • Enterprise connectors
  • Data pipelines
  • Security framework
  • Monitoring setup
  • Performance optimization

OneLake data architecture

Design and implement unified data lake architecture with OneLake as the foundation

  • OneLake architecture design and governance
  • Data lake organization with medallion architecture
  • Cross-workspace data sharing and security
  • Delta Lake optimization and performance tuning
  • Data mesh implementation patterns
  • Multi-tenant data isolation strategies
Key deliverables
  • OneLake architecture
  • Data governance framework
  • Security model
  • Performance optimization

Fabric data pipelines

Build enterprise-scale data pipelines using Fabric's native orchestration

  • Data Factory pipeline migration to Fabric
  • Real-time data ingestion with Event Streams
  • Complex ETL/ELT pipeline development
  • Pipeline monitoring and alerting
  • Cross-platform data integration
  • Hybrid cloud-on-premises orchestration
Key deliverables
  • Production pipelines
  • Monitoring dashboards
  • Error handling
  • Documentation

Lakehouse/Warehouse implementation

Deploy and optimize Fabric Lakehouses for analytics and AI workloads

  • Lakehouse architecture and design
  • SQL endpoint optimization
  • Spark compute configuration
  • Data modeling for analytics
  • Performance tuning and optimization
  • Multi-workload isolation and scaling
Key deliverables
  • Lakehouse environment
  • SQL endpoints
  • Spark configurations
  • Performance reports

Power BI integration

Seamless integration between Fabric data assets and Power BI reporting

  • Direct Lake mode implementation
  • Semantic model optimization
  • Real-time dashboard development
  • Fabric-native Power BI datasets
  • Cross-workspace report sharing
  • Enterprise-scale report deployment
Key deliverables
  • Power BI datasets
  • Real-time dashboards
  • Semantic models
  • User training

Security & compliance

Enterprise-grade security and compliance implementation across Fabric workloads

  • Row-level security implementation
  • Column-level encryption and masking
  • Azure AD integration and RBAC
  • Compliance framework implementation
  • Data lineage and audit trails
  • Cross-tenant security policies
Key deliverables
  • Security Framework
  • Compliance Reports
  • Audit Systems
  • Access Controls
Real challenges our consulting team addresses

Typical systems integrated with Fabric

ERP systems

  • SAP ECC 6.0 Timeline: 6-10 weeks
  • SAP S/4HANA Timeline: 4-8 weeks
  • Oracle EBS Timeline: 6-12 weeks
  • Microsoft Dynamics 365 Timeline: 3-6 weeks
  • PeopleSoft Timeline: 8-14 weeks
  • JD Edwards Timeline: 6-10 weeks

CRM & sales

  • Salesforce Timeline: 2-4 weeks
  • HubSpot Timeline: 1-3 weeks
  • Microsoft Dynamics CRM Timeline: 2-4 weeks
  • ServiceNow Timeline: 4-8 weeks
  • Zendesk Timeline: 1-3 weeks
  • Workday Timeline: 4-8 weeks

Cloud & SaaS

  • AWS RDS/Redshift Timeline: 2-4 weeks
  • Google BigQuery Timeline: 1-3 weeks
  • Snowflake Timeline: 2-4 weeks
  • MongoDB Atlas Timeline: 3-6 weeks
  • Databricks Timeline: 4-8 weeks
  • Tableau Server Timeline: 2-4 weeks

Why Microsoft Fabric

Key advantages of the unified analytics platform

Unified platform

Single platform for all data and analytics needs

  • Reduced complexity and management overhead
  • Consistent security and governance model
  • Simplified user experience and training
  • Lower total cost of ownership
OneLake foundation

Centralized data lake with automatic optimization

  • Automatic data organization and optimization
  • Cross-workspace data sharing without movement
  • Built-in security and compliance controls
  • Simplified data governance and lineage
Enterprise integration

Native connectivity to 300+ enterprise systems

  • SHIR-based hybrid connectivity
  • Real-time and batch integration patterns
  • Enterprise-grade security and compliance
  • Simplified integration management
Capacity-based pricing

Predictable costs with flexible compute allocation

  • 30-50% cost reduction vs. traditional licensing
  • Flexible capacity allocation across workloads
  • No per-user licensing for data engineering
  • Automatic scaling and optimization

Microsoft Fabric workloads

Complete expertise across all Fabric components

Data factory

Enterprise data integration and orchestration

Use cases:

  • ERP integration
  • Cloud migration
  • Real-time sync
  • Batch processing

Key features

  • 200+ native connectors
  • Hybrid data integration
  • Monitoring and alerting
  • Git integration and CI/CD

Synapse data engineering

Apache Spark-based big data processing

Use cases:

  • Data transformation
  • ML feature engineering
  • Security Model
  • Streaming analytics

Key features

  • Serverless Spark pools
  • Notebook-based development
  • Delta Lake support
  • ML integration
  • Auto-scaling compute

Synapse data warehouse

Cloud-native data warehouse with T-SQL

Use cases:

  • Enterprise DW
  • Analytics workloads
  • Error Handling
  • Historical analysis

Key features

  • Serverless and dedicated pools
  • Columnar storage
  • Workload isolation
  • Security and compliance
  • Cross-database queries

Real-time analytics

KQL-based streaming analytics and monitoring

Use cases:

  • IoT analytics
  • Log analysis
  • Monitoring
  • Real-time alerts

Key features

  • KQL query engine
  • Time-series analytics
  • Real-time dashboards
  • Anomaly detection
  • IoT data processing

Data science

End-to-end ML lifecycle management

Use cases:

  • Predictive analytics
  • Real-time Dashboards
  • AI/ML pipelines
  • Data exploration

Key features

  • MLflow integration
  • Automated ML
  • Model deployment
  • Experiment tracking
  • Collaborative notebooks

Power BI

Business intelligence and visualization

Use cases:

  • Executive dashboards
  • Self-service BI
  • Embedded analytics
  • Mobile reporting

Key features

  • Direct Lake mode
  • Semantic models
  • Real-time dashboards
  • Natural language queries
  • Mobile optimization
Common migration paths and considerations

Migration to Fabric

From To Complexity Timeline Key Benefits Considerations
SAP ECC 6.0 On-premises Fabric via SHIR Medium 6–10 weeks
  • Real-time SAP data
  • Unified analytics
  • SHIR deployment
  • SAP security
Oracle EBS On-premises Fabric via SHIR Medium 6–12 weeks
  • Cloud scalability
  • Real-time insights
  • Oracle licensing
  • Data volumes
Legacy Mainframe Fabric Lakehouse High 12–20 weeks
  • Modernization
  • Cost reduction
  • Data migration complexity
  • Legacy system dependencies
Multi-cloud Data Lakes Fabric OneLake Medium 8–16 weeks
  • Unified platform
  • Simplified management
  • Data movement costs
  • Security alignment
Azure Data Factory Fabric Data Factory Low 2–4 weeks
  • Unified platform
  • Better monitoring
  • Pipeline compatibility
  • Connector availability

Implementation approach

Proven methodology for Fabric deployments

01

Assessment & planning

Duration: 3-6 weeks

Comprehensive evaluation of enterprise systems and Fabric readiness

Key activities

  • Enterprise architecture assessment
  • Fabric capacity planning and sizing
  • SHIR deployment strategy
  • Security and compliance review
  • Collaborative notebooks

02

Foundation setup

Duration: 4-8 weeks

Establish Fabric environment and OneLake architecture

Key activities

  • Fabric capacity provisioning
  • OneLake architecture implementation
  • SHIR deployment and configuration
  • Security and governance setup
  • Workspace organization and permissions

03

Enterprise integration

Duration: 8-16 weeks

Connect enterprise systems and implement data pipelines

Key activities

  • Enterprise system connectivity setup
  • Data pipeline development and testing
  • Historical data migration
  • Real-time integration implementation
  • Data quality validation and monitoring

04

Analytics enablement

Duration: 4-8 weeks

Connect enterprise systems and implement data pipelines

Key activities

  • Lakehouse and warehouse setup
  • Power BI integration and optimization
  • Real-time analytics implementation
  • User training and adoption
  • Performance optimization
Modernizing analytics with microsoft Fabric

Case study

TMS International, a global leader in steel services and materials management, operates with multiple Dynamics 365 Finance & Operations (F&O) and AX on-premises systems across its divisions. To support its large-scale data needs, TMS had been using Azure Synapse pipelines for ETL and storage and Power BI Premium for enterprise reporting. With growing demands for scalability, cost efficiency, and a modern analytics platform, TMS partnered with our team to conduct a detailed migration assessment to Microsoft Fabric, ensuring the platform was future-ready and more cost-effective than the existing setup.

Business challenges

  • Complex data landscape: Multiple D365 F&O and AX instances created fragmented pipelines and duplicate models.
  • High maintenance costs: Separate Synapse + Power BI Premium architecture was expensive to operate and scale.
  • Performance limitations: Growing reporting user base impacted refresh performance and latency.
  • Future-readiness: The existing platform lacked built-in capabilities for AI, unified governance, and direct integration with evolving Microsoft services.

Business outcomes

  • Cost savings: Reduced licensing and infrastructure spend by consolidating services into Fabric.
  • Performance gains: Faster reporting experience with Direct Lake mode for thousands of users
  • Simplified operations: Unified pipeline and reporting architecture lowered maintenance overhead.
  • Future-proof platform: Fabric provides flexibility for AI, predictive analytics, and enterprise-scale governance.

Why microsoft Fabric for TMS international

  • End-to-end platform (data ingestion, storage, modeling, reporting, governance in one).
  • Cost efficiency compared to running Synapse + Power BI Premium.
  • Seamless integration with multiple D365 instances.
  • AI-ready with Copilot and advanced analytics capabilities.

Migration assessment and solution

We performed a comprehensive migration analysis to evaluate cost, scalability, and modernization benefits of adopting Microsoft Fabric.

Key migration findings

  • Unified platform: Fabric replaces multiple services (Synapse, Data Lake, Premium capacity) with a single SaaS solution.
  • Lower TCO: Significant cost savings by eliminating redundant infrastructure and optimizing Power BI capacity usage.
  • Scalable data integration: Fabric pipelines with direct connectivity to multiple D365 instances, reducing complexity.
  • Direct lake mode: Enabled faster query performance by bypassing import/refresh bottlenecks.
  • Future-ready features: AI-driven analytics, integrated governance via Purview, and one-click scale-out capabilities.

Migration roadmap

  • Assessment – Inventory of all Synapse pipelines, data models, and Power BI Premium capacities.
  • Proof of concept – Migration of Finance and AX data into Fabric Lakehouse.
  • Architecture blueprint – Unified Lakehouse + Warehouse model for finance and operational reporting.
  • Phased migration – Move workloads from Synapse to Fabric, validating performance and cost savings.
  • Decommission legacy services – Gradually sunset Synapse and Power BI Premium, fully adopting Fabric.
Driving enterprise-wide analytics with Microsoft Fabric and dynamics 365

Case study

KBR, one of the largest project implementation companies in North America, manages large-scale engineering, procurement, and construction projects across industries. With thousands of employees spread across multiple regions, timely access to project, financial, and operational data was critical. KBR partnered with our team to design and implement a unified analytics and reporting solution on Microsoft Fabric, seamlessly integrated with Dynamics 365 Finance & Operations (F&O) and Dynamics 365 Project Operations (ProjOps).

Business challenges

  • Fragmented reporting landscape: Multiple reporting tools and data silos across finance, project execution, and resource planning.
  • Slow data access: Users relied on manual extracts or performance-heavy reports directly from D365, causing delays.
  • Scalability issues: With thousands of report consumers, the existing reporting infrastructure could not meet performance or concurrency demands.
  • Limited self-service: Business users lacked the ability to explore data beyond predefined reports.

Business outcomes

  • Single source of truth: Unified reporting across Finance and Projects with consistent KPIs.
  • Improved decision-making: Real-time insights into project profitability, costs, and resource utilization.
  • High user adoption: Hundreds of active users seamlessly accessing reports in Microsoft Fabric.
  • Operational efficiency: Reduced manual data wrangling and accelerated reporting timelines from days to minutes.
  • Future-Ready architecture: Scalable Fabric foundation to incorporate additional workloads ( HR, legacy systems).

Why Microsoft Fabric

  • Native D365 integration for both Finance & ProjOps.
  • Direct lake mode ensuring lightning-fast performance at enterprise scale.
  • Built-in governance & security aligned with global compliance standards.
  • Unified platform reducing dependency on multiple BI/reporting tools.

Solution: Microsoft Fabric implementation

We implemented an enterprise-grade analytics platform using Microsoft Fabric with direct integration to Dynamics 365 F&O and ProjOps.

Key components

Data integration layer

  • Continuous pipelines from D365 F&O and ProjOps into Fabric’s Lakehouse.

Data modeling & governance

  • Standardized semantic models built in Fabric for Finance, Projects, Procurement and Resource Management.
  • Applied Row-Level Security (RLS) for role-based access across global teams.

Analytics & reporting

  • Hundreds of users consuming insights through Power BI reports hosted on Fabric.
  • Pre-built dashboards for project profitability, resource utilization, cost tracking, and cash flow.
  • Self-service data exploration enabled for finance and project managers.

Performance & scale

  • Optimized Direct Lake mode in Fabric to deliver instant report performance without query latency.
  • Elastic scalability to support thousands of concurrent users across regions.

Transform your enterprise data landscape with Microsoft Fabric’s unified analytics platform. We deliver end-to-end implementations from architecture design and enterprise system integration to advanced analytics and AI enablement. Our expertise spans the complete Fabric ecosystem – from OneLake data architecture and SHIR-based connectivity to real-time streaming, lakehouse optimization, and Power BI integration at enterprise scale.

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