Enter your search text in the box above

Select a result to preview

AI-Driven MDM on Microsoft Fabric: Build the Intelligent Golden Record

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

Description

Discover how to build an AI-powered Master Data Management solution on Microsoft Fabric. Learn how AI models identify duplicates, enrich data, and create a reliable golden record. See practical patterns that improve data quality, downstream analytics, and enterprise operational efficiency.

Key Takeaways

My Notes

Action Items

Slides

📥 Download Slides

AI Driven MDM on
Microsoft Fabric:
Build the Intelligent
Golden Record
Mehul Thacker
Principle Consultant, DynaTech Systems
What Is MDM?
Modern organizations
rely on many business
systems — from ERPs
and CRMs to
accounting and
support tools like
QuickBooks, GP, or
Dynamics.
Each stores related
information about the
same customers or
vendors, but details
often differ — names,
addresses, and IDs
rarely align.
Master Data
Management (MDM)
connects these
systems, cleans and
merges their records,
and creates one
centralized, accurate
“golden record”.
This trusted data
foundation ensures
every team and
application works with
the same reliable
information.
The Data Reality
Today’s Data Challenge
• Across the enterprise, master data is often duplicated, inconsistent, and constantly evolving.
Organizations commonly face challenges such as
Duplicate records across systems
Inconsistent data formats and attributes
Frequent manual updates and corrections
The same customer, vendor, or product often appears
in multiple versions across ERP, CRM, and operational
systems.
Variations in names, addresses, product codes, and
identifiers create conflicting records.
Manual data edits across departments often introduce
inconsistencies.
Complex third-party integrations
Address changes and missing information
Limited visibility across business systems
Data flowing between ERP, CRM, and external systems
can create mismatched or incomplete records.
Frequent address corrections and incomplete fields
make it harder to maintain accurate master data.
Without unified master data, organizations struggle to
get a consistent enterprise-wide view.
•
Delayed reporting and reconciliation efforts
•
Reduced trust in enterprise data
•
Integration errors across enterprise systems
•
Compliance Risk
What DynaTech Offers
What DynaTech Offers: Accelerated MDM Framework on Microsoft Fabric
• DynaTech provides a pre-built Master Data Management framework designed to help organizations rapidly establish a trusted data foundation for Analytics and AI
Standardized Common Data Model
(CDM) aligned with enterprise
business processes
Predefined Master Data Entities
across core business domains
Pre-built end-to-end CDM models
for Dynamics 365 F&O, enabling
faster implementation for Dynamics
customers.
Industry-ready KPI Models and
Dashboards for faster business
insights
Built-in Data Quality Framework for
validation, governance, and
consistency
Built on Microsoft technologies
with flexible customization
Microsoft Fabric-based architecture
enabling scalable data engineering
and analytics
This framework enables organizations to accelerate implementation, improve data quality, and quickly deliver business-ready analytics.
Business Value Realization with AI-Driven MDM
Single trusted Golden
Improved data quality and Faster and more reliable
Reduced manual data
Foundation for AI-driven
Customer Record across
elimination of duplicate
sales analytics and
reconciliation across
insights and intelligent
enterprise systems
customer records
dashboards
teams and systems
decision-making
MDM Architecture
How DynaTech Does MDM
› Fabric integrates 145+ sources via
Dataflow Gen2 & Data Factory.
› Databases: SQL, PostgreSQL, SAP, Oracle,
MySQL, Redshift, BigQuery, Snowflake, etc.
› Storage: Azure Blob/Data Lake, S3, GCS,
Oracle Cloud
› Apps: Dynamics, Salesforce, ServiceNow,
SharePoint, Dataverse
› Protocols: FTP/SFTP, HTTP, REST, File
System
› Benefit: Unifies all your siloed data in one
place.
INGEST
› AI-powered rule suggestions,
metadata-driven validation, and BI
dashboards for data quality review.
› Benefit: Errors fixed, duplicates
removed — your data is now
analysis-ready.
PROFILE
› Metadata-driven notebooks enable
continuous data profiling to detect
anomalies, errors, and outliers.
› Benefit: Gain a measurable,
trackable KPI for enterprise data
quality.
CLEAN
› Ensure uniformity by standardizing data
(e.g., employee names in CRM using SAP
master).
› Benefit: Enables consistent, shareable
data—no more duplicate entries like ‘USA’,
‘United States’, and The US’. ‘
ENRICH
› Easy POST API module in Fabric
enriches address data in customer
master via MDM.
› Benefit: Automates filling gaps at
scale—boosts reporting accuracy
and saves time.
STANDARDIZE
› Distribute consolidated master data to all
required systems for consistency.
› Enable real-time data sync from MDM to
connected applications and analytics
platforms.
› Benefit: Keeps downstream systems
continuously updated — ensuring data is
always accurate, accessible, and ready for
business use.
› Delivers insight-ready information for faster
reporting and better decision-making.
DISTRIBUTE
& STREAM
CONSOLIDATE
› MDM creates a golden record by
consolidating customer data from
SAP & CRM into Fabric’s Silver layer.
› Benefit: High-quality, authoritative
data—securely accessible to
systems and users.
RAW SOURCE DATA FLOWS INTO
YOUR MDM PLATFORM
INSIGHT READY DATA IS FED INTO
YOUR ANALYTICS ENGINE
Ensuring High-Quality Customer Master Data
• To support accurate analytics and business KPIs, DynaTech’s MDM framework applies predefined data quality controls on Customer Master data.
Key validation rules include
Uniqueness Controls
Each customer must have a unique identifier and
account number to prevent duplicate records.
• Customer Record ID must be unique
• Customer Unique
• Account Number Reuse Check
Mandatory Field Validation
Critical attributes such as Customer Account, Currency
Code, and Customer Group must be populated.
• Customer Record ID must not be empty
• Customer Account Number must not be empty
• Currency Code must not be empty
• Customer Group must not be empty
Referential Integrity Validation
Format & Pattern Validation
Customer records must reference valid master data such
as currency codes and customer groups..
• Customer Group must exist in submaster
Customer account numbers, names, and attributes
follow standardized formats and validation rules.
• Account Number must follow defined pattern
• Currency must exist in Currency Master
• Customer Name must be text type
• Enum values must match system-defined codes
• Character length validation
These validations ensure trusted customer master data, enabling reliable analytics, dashboards, and operational reporting.
Transforming Master Data into Actionable Business Insights
• With governed and standardized master data, organizations can generate consistent KPIs and business insights across operational systems.
• DynaTech’s framework enables organizations to transform master data into business-ready analytics and dashboards.
Examples include
• Sales Order Performance Metrics
• Customer Demand and Growth Trends
• Product Performance Insights
• Operational Delivery Metrics (OTIF)
• Return Order and Customer Behavior Analysis
Order & Sales Performance
Trend & Growth Analysis
Customer & Product Insights
KPI
Business Impact
KPI
Business Impact
KPI
Business Impact
Total Orders
Shows number of unique customer orders and true
demand
Total Sales by
Month
Tracks fiscal performance and sales trends
Unique
Customer
Shows number of unique customer orders and true
demand
Total Sales
Measures overall revenue generated
Total Quantity
Reflects total sales volume and demand level
Unique
Product
Reflects total sales volume and demand level
Revenue
Ensures accurate line-level revenue and profitability
analysis
Average Product
Revenue
Ensures accurate line-level revenue and profitability
analysis
YoY %
Outstanding
Amount
Highlights year-over-year growth or decline
Average
Customer
Revenue
Measures overall revenue generated
These insights enable organizations to improve operational visibility and make faster, data-driven decisions.
Sales Performance Dashboard
• With standardized customer and product master data, organizations can build interactive dashboards that provide real-time visibility into sales performance.
This dashboard enables business users to analyze
Sales Performance Metrics
• Total Sales and Revenue
• Total Orders and Sales Quantity
• Unique Products Sold
Sales Trends
• Monthly sales performance
• Year-over-Year sales growth
Customer & Product Insights
• Product demand analysis
• Customer purchase patterns
Geographical Performance
• Sales distribution by location
These insights help organizations monitor business performance, identify trends, and make faster data-driven decisions.
Sales Performance Dashboard
Sales Order Performance: Return Analysis
• Beyond overall sales performance, governed master data also enables detailed operational analytics across the sales lifecycle.
• This example highlights Return Order Performance, helping organizations monitor product returns and identify operational issues.
The dashboard provides insights into
Return Performance Metrics
• Total Return Quantity
• Total Return Amount
• Return Rate %
• Return Impact %
Trend Analysis
• Return trends over time
• Identification of increasing return
patterns
Product Insights
• Top returned products
• Products with higher defect or
return rates
Customer-Level Analysis
• Customer-wise return orders
• Item-level return quantities and values
Sales Order Performance: Return Analysis
Master Data Domains Supported by DynaTech MDM
• DynaTech’s MDM framework provides predefined models and governance controls for key enterprise master data entities, enabling organizations to establish a consistent and
trusted data foundation.
The framework includes standardized models and validation rules for
Customer Master
Product / Item Master
• Unified customer identities across CRM, ERP, and
operational systems.
• Standardized product definitions supporting
inventory, sales, and production processes.
Vendor Master
Location / Address Master
• Centralized vendor records enabling consistent
procurement and financial operations.
• Validated and enriched address data to ensure
operational accuracy.
Financial Master
Asset Master
• Governed financial structures including chart of
accounts and financial dimensions.
• Centralized asset information supporting
lifecycle tracking and financial reporting.
Transforming Master Data into Actionable Business Insights
• With governed and standardized master data, organizations can generate consistent KPIs and business insights across operational systems.
• DynaTech’s framework enables organizations to transform master data into business-ready analytics and dashboards.
Examples include
Customer
Demand
and Growth
Trends
Sales Order
Performance
Metrics
Operational
Delivery
Metrics
(OTIF)
Product
Performance
Insights
Return
Order and
Customer
Behavior
Analysis
DynaTech configured Applications with Fabric
Various Data Bases & Applications DynaTech has configured with Fabric
Azure Blob
Storage
File System
ERP Systems & Business Applications
File Storage & Transfer Systems
Azure SQL
Database
HTTP
REST
Azure SQL
Managed
Instance
Datalake
SQL
Database
(Preview)
Azure
Database
For MySQL
Communication Protocols & Data Interfaces
Dataverse
Databases
Social Media Platforms
Documents & File Types
Analytics & Reporting Tools
Specialized Data Standards
Demo Walkthrough: Customer Master Example
ABC Corp
ABC Corp Ltd
ABC Corporation
MDM Farmwork
Golden Customer Record
ABC Corporation
Demo Walkthrough- Bronze Layer - Ingesting Enterprise Data
What Happens
› Data from enterprise systems such as Dynamics 365, NetSuite, and CRM platforms is ingested into Microsoft Fabric using different connectors like Fabric Link, API,
ADLS Gen2, SharePoint / OneDrive, Azure Synapse / Data Warehouse, etc.
› Raw data from multiple operational systems is consolidated into a single centralized data platform.
› Source data is preserved in its original structure to maintain traceability and lineage.
Business Outcome
› Enterprise data from multiple systems becomes accessible in one unified environment.
› Eliminates fragmented data silos across ERP, CRM, and external applications.
› Establishes the foundation for data governance and downstream processing
Demo Walkthrough- Silver Layer – Master Data Preparation &
Standardization
What Happens
› Raw data from the Bronze layer is profiled and transformed to create clean and standardized master data.
› Data profiling analyzes source data and classifies it into master entities (customers, vendors, products) and transactional entities (orders, invoices).
› Predefined validation rules detect and correct issues such as missing values, duplicates, invalid formats, and inconsistent records.
› Customer data from multiple systems is standardized, enriched, and consolidated to create a single trusted Customer Master dataset. E.g.Sales Header
› A manage-level approval workflow validates the cleaned, standardized, and consolidated data before it is promoted to the next layer.
Business Outcome
› Creation of clean and governed Customer Master data across enterprise systems.
› Consistent and standardized data formats for accurate reporting and analytics.
› Trusted master data foundation ready for dashboards, KPIs, and AI-driven insights.
Demo Walkthrough- Gold Layer - Business Analytics
and Insights
What Happens
› Clean master data from the Silver layer is transformed into business-ready analytical models.
› Semantic models are created to support reporting and analytics.
› Data models combine fact tables (Fact_Sales) with dimension tables (Dim_Customer).
Business Outcome
› Business users can access trusted data through Power BI dashboards and Excel reports.
› Enables consistent KPIs and performance metrics across the organization.
› Delivers analytics-ready data to support operational and strategic decision making.
Questions & Answers
Sound off.
The mic is all yours.
Influence the product roadmap.
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