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Transform your data platform into an AI-ready foundation for growth

#fabcon2026 #session #learning #microsoft #fabcon2026-session

Description

Modernize your end-to-end data platform to Fabric and unlock AI/ML enabled potential in workloads, analytics, and collaboration.
During this session, we will focus on agentic AI methods of automation during the migration process, achieving 60% improvement in productivity.

Key Takeaways

My Notes

Action Items

Slides

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Transform Your Data Platform into an AI-Ready
Foundation for Growth
Booth #409
Ravi Gunturu
Rahul Athalye
VP and Market Head of Data and AI
VP and Service Line Head, Data & Analytics
ravi.gunturu@bitwiseglobal.com
rahul.athalye@bitwiseglobal.com
AI Is Creating a New Enterprise Data Reality
What Enterprises Are Building
• GenAI copilots for productivity
• AI agents for workflow automation
• Intelligent, insight-driven applications
• Conversational analytics interfaces
• Autonomous operational systems
Booth #409
Most enterprise data
environments were
designed for reporting
and BI — not AI.
AI Use Cases Customers Are Actively Pursuing
Each represents a strategic priority — and each places unique demands on the underlying data platform.
Booth #409
Intelligent
Decisioning
GenAI Knowledge
Platforms
Autonomous
Operations
Conversational
Analytics
• Forecasting & demand
planning
• Enterprise copilots &
document intelligence
• AI agents for workflow
automation
• Natural language BI
interfaces
• Risk scoring & pricing
optimization
• Semantic search &
RAG applications
• Fraud detection &
supply chain
optimization
• Executive AI copilots &
self-service insights
Every one of these use cases requires trusted, governed, and unified data as its foundation.
Transforming the Data Platform for AI-Driven Scale
Modernizing Data
Architectures
Automated MetadataAware Pipelines
Re-architect legacy siloed systems
to a unified, distributed, cloudnative platform for AI/ML
workloads.
Shift from manual ETL to
dynamic, metadata-aware
pipelines that adapt to changing
data sources.
GPU-Accelerated Compute
and Storage
Federated Governance and
Real-Time Ingestion
Use scalable compute with GPU
acceleration and highperformance shared storage to
optimize AI workloads.
Enable federated governance and
event-based real-time ingestion
pipelines for autonomous yet
standardized data domains.
Booth #409
Two Paths to AI-Ready Platforms
Booth #409
Enterprises pursuing AI-ready data foundations typically follow one of two
distinct transformation journeys — each with its own set of challenges,
priorities, and acceleration needs.
Path 1 — Data Platform Modernisation
Path 2 — Greenfield AI Data Platform
Legacy → Modern
Build new alongside legacy
Migrate existing platforms to Microsoft
Fabric:
Construct a modern AI data platform from the
ground up, purpose-built for AI workloads:
• Teradata → Fabric
• Snowflake → Fabric
• Informatica → Fabric
• Lakehouse architecture
• Real-time and streaming data
• Unstructured data ingestion
• AI-native pipelines
Key challenges:
Both journeys require: automation and
engineering acceleration to be viable at
enterprise scale.
• Migration risk & code conversion
• Pipeline redesign at scale
• Minimising business disruption
Large-scale data modernization is not a project — it is a program. The sheer
scale of makes manual migration creates prohibitive cost, extended
timelines, and unacceptable delivery risk.
Agentic AI driven data modernization to Microsoft Fabric
Source Systems
Target Environment
DB Objects Conversion
• Oracle
• SQL Server
ETL Conversion
• AB Initio,
• Informatica,
• SSIS,
• DataStage
• ADF,
• Synapse Pipeline
BI Conversion
• SSRS
• Tableau
• Cognos*
Script Conversion
• Unix Shell
Analyze
Data Validation
Convert
Booth #409
• Faster, lower-risk
migrations
• Higher engineering
productivity
• AI-ready data platforms
from day one
• Accelerated time-tovalue for AI initiatives
• Improved and
measurable data
quality
Validate
• Oracle
• PostgreSQL
• Big Query
• Snowflake
• SQL Server
• Csv, Parquet
• Amazon Redshift • Synapse
• MySQL
• Delta Lake
75%
90%
100%
70%
80%
80%
Reduction in
Migration Cost
Touch Free
Conversion
Accuracy
Reduction in
Migration Time
Boost in Developer’s
Productivity
Efforts saved on
Data Validation
Agentic AI driven data modernization to Microsoft Fabric
Discovery
Code
Translation
• Autonomous Data discovery
• Code Conversion
• Semantic Intent Derivation
• Reconstruction of code and
SQL workloads into Fabric
formats
• Optimized Data and
Dependency Mapping
• Complexity Scoring
• Multi-Agent Orchestration –
Interpreting complex logic
Pipeline
• Automated creation of
Lakehouse Delta tables and
shortcuts
• Data Factory Pipelines
Governance
• Register metadata and build
lineage graphs
• Git-enabled workspaces
and CI/CD integration
• Semantic Model Generation
• Collaborate across shared
notebooks, pipelines, and
semantic models
• No native
transformations in
Fabric data pipelines
• Co-pilot accesses both
Storage and compute
planes and is metadata
aware
• Universal end to end
lineage view
• Fine Grain Controls (
Row, Column , Object
Level)
Booth #409
Validation
• Automated unit tests, parity
queries, and schema
checks ensure correctness
• Runtime checks and data
quality rules
• Validate data parity and
detect anomalies to ensure
correctness
Adopting to Fabric architecture
• OneLake Universal
storage
• Virtualized data access
with Onelake shortcuts
• Logic distributed across
Fabric engines
• Cross workspace
queries
• Data Quality in Purview
Unified Catalog,
• Pipeline Embedded
validation
• Observability for drift
monitoring
Key Takeaways
AI Requires New Data Architectures
GenAI, agents, and intelligent applications
demand architectures built for diverse, semantic,
real-time data — not legacy BI-optimised
platforms.
Microsoft Fabric Provides a Unified Foundation
Fabric's integrated, end-to-end architecture
eliminates fragmentation and delivers the
governance, scale, and AI-readiness enterprises
need.
Booth #409
Modernize Legacy Platforms with Urgency
The window to modernize is now. Organizations
that delay will find their AI ambitions constrained
by outdated infrastructure and accumulated data
debt.
Automation Accelerates Transformation
Accelerators like FulcrumCloud compress
timelines and reduce risk — making enterprisescale modernisation achievable within businessrealistic timeframes.
The future of enterprise AI will belong to organisations that build AI-ready data foundations today.
Sound off. The mic is all yours. Influence the product roadmap.
Booth #409
Join the Fabric User Panel
Join the SQL User Panel
Share your feedback directly
with our Fabric product group
and researchers.
Influence our SQL roadmap and
ensure it meets your real-life needs
https://aka.ms/ JoinFabricUserPanel
https://aka.ms/JoinSQLUserPanel