Data Management
Master Data Management Services
Create one trusted, continuously maintained record for every customer, product, supplier and location, and share it with every system that depends on it.
One Golden Record for Your Core Business Entities
The same customer appears in CRM as “Acme Corp.”, in ERP as “ACME Corporation Ltd” and in the support desk under a former employee’s email. Products carry different names, units and categories in procurement, the warehouse and the online store. Each system works on its own, but together they create duplicate shipments, inconsistent pricing, inaccurate revenue per customer and analytics that cannot be reconciled.
Master data management resolves this by matching records across sources, merging them into golden records according to agreed survivorship rules, and distributing the result back to operational and analytical systems. Hanoi Technology designs and implements MDM that fits your architecture, choosing the right implementation style, platform and stewardship workflows so the golden record stays accurate long after go-live.
The Challenge
Why Master Data Becomes Fragmented
Master data problems accumulate quietly as organizations grow.
Every System Creates Its Own Records
CRM, ERP, e-commerce, billing and support platforms each allow users to create customers or products independently, with no check for existing records.
Mergers and New Channels
Acquisitions, new regions and marketplaces add systems with different identifiers, formats and hierarchies that must be reconciled.
Matching Is Harder Than It Looks
Typos, abbreviations, transliteration, shared addresses and changed company names make exact matching unreliable and naive fuzzy matching risky.
No One Owns the Golden Record
Without stewardship processes, merged records degrade as new duplicates and edits arrive, and the MDM hub loses credibility.
Business Value
What Master Data Management Delivers
A True 360-Degree View
Sales, service and marketing see the full relationship with each customer, including accounts, contacts, orders and interactions across systems.
Accurate Analytics
Revenue, margin and spend roll up correctly by customer, product and supplier because each entity is counted once with consistent hierarchies.
Faster Onboarding
New customers, products and suppliers are created once with validated data and shared automatically, reducing manual entry and delays.
Lower Operational Waste
Duplicate mailings, payments, shipments and inventory errors drop when every system references the same master record.
Better Compliance and Risk Control
Consistent party data supports KYC, sanctions screening, consent management and regulatory reporting.
A Reusable Foundation for AI
Clean, linked entities improve recommendation, forecasting and generative AI use cases that need reliable context.
MDM Is a Business Program with a Technical Core
Successful MDM programs are owned by the business, with clear data domains, owners and stewardship. Technology handles matching and synchronization at scale, but the rules for what makes a record correct and who may change it must come from the people who run the processes.
Our Services
Hanoi Technology’s End-to-End Master Data Management Services
End-to-end MDM services, from strategy through operation.
MDM Strategy and Readiness
We identify the domains with the highest value, assess source systems and data quality, and define a business case and phased roadmap.
- Domain prioritization
- Source-system and quality assessment
- Business case and roadmap
Architecture and Style Selection
We select the right implementation style, whether registry, consolidation, coexistence or centralized, based on your systems, latency needs and organizational readiness.
- Implementation style recommendation
- Target architecture
- Platform evaluation and selection
Data Modeling and Hierarchies
We design master data models, relationships and hierarchies, such as corporate parent-child structures, product taxonomies and location hierarchies.
- Master data model
- Hierarchy design
- Attribute standards
Match, Merge and Survivorship
We configure deterministic and probabilistic matching, tune thresholds with real data samples and define rules that decide which source wins for each attribute.
- Matching rules and thresholds
- Survivorship rules by attribute
- Match quality test results
Integration and Synchronization
We connect the hub to source and consuming systems through APIs, events or batch integration so golden records flow where they are needed.
- Inbound and outbound integrations
- Cross-reference of source IDs
- Real-time or batch publication
Stewardship and Operations
We set up workflows for review queues, merge and unmerge decisions and change approvals, and can operate MDM as a managed service.
- Stewardship workflows and UI
- Data quality dashboards
- Managed MDM operations
Our Approach
Our MDM Implementation Roadmap
We deliver MDM in increments, starting with the domain and use case that matter most.
- 01
Define Scope and Value
We select a first domain and concrete outcomes, such as a deduplicated customer base for marketing or a supplier master for procurement analytics.
Deliverables: Scope definition · Success metrics
- 02
Profile Sources and Model Data
We profile every contributing source, document identifiers and attributes, and design the master model and hierarchies.
Deliverables: Source profiling report · Master data model
- 03
Configure Matching and Survivorship
We build and tune match rules on representative samples, review results with business users and agree survivorship logic.
Deliverables: Tuned match rules · Signed-off survivorship rules
- 04
Integrate and Migrate
We load and consolidate historical data, connect systems and run parallel validation before switching consumers to the golden record.
Deliverables: Initial golden record load · Integrated systems
- 05
Govern and Expand
We launch stewardship processes, monitor match quality and duplicates, and extend MDM to further domains and systems.
Deliverables: Stewardship operating model · Next-domain plan
Use Cases
Master Data Management Use Cases
Where MDM makes a measurable difference.
Customer 360 for B2C Brands
A consumer brand links store, web, app and loyalty profiles into one customer record to power consistent personalization.
B2B Account Hierarchies
A B2B supplier models parent companies, subsidiaries and sites so sales sees total account revenue and credit exposure correctly.
Product Master for Omnichannel Retail
A retailer manages product attributes, variants and categories centrally and publishes them to stores, web and marketplaces.
Supplier Master for Procurement
A manufacturer consolidates vendors across plants and ERP instances, revealing duplicate suppliers and improving negotiating leverage.
Patient and Provider Records
A healthcare network matches patient and provider records across clinics to reduce duplicate charts and improve care coordination.
Property and Location Data
A real estate platform links listings, buildings and addresses across data feeds to avoid duplicate properties and improve valuation inputs.
Technology
MDM Platforms and Tools
We work with leading MDM platforms as well as cloud-native and custom approaches.
- Informatica MDM SaaS
- Reltio
- Profisee
- Ataccama ONE MDM
- Semarchy xDM
- Stibo Systems STEP
- SAP Master Data Governance
- Tamr
- Microsoft Purview
- Databricks
- Snowflake
- Splink
- Zingg
- Apache Kafka
- MuleSoft
Platforms
Deliver Master Data Management on Your Preferred Platform
- InformaticaEnterprise data integration, quality and governance.Explore
- AtaccamaData quality, governance and master data in one platform.Explore
- DatabricksUnified lakehouse for data engineering, analytics and AI.Explore
- SnowflakeElastic cloud data platform for analytics and data sharing.Explore
- Microsoft AzureModernize data, analytics and AI within your Azure tenant.Explore
Why Hanoi Technology
Why Organizations Choose Hanoi Technology
Senior, Cross-Functional Teams
Strategy, data, AI, cloud and engineering specialists work as one team, so nothing is lost between hand-offs.
Proven Delivery
More than 50 projects delivered for clients in North America, Europe and Asia-Pacific.
Radical Transparency
A written update every week and a demo of working software every sprint, so you always know where things stand.
Cost-Effective Global Delivery
Experienced engineers from our Hanoi delivery hub, with working-hour overlap for every major time zone.
Success Story · Real estate
Property discovery and lead conversion for a US real estate marketplace
A US marketplace connecting buyers, sellers and agents had plenty of traffic but few enquiries. We built personalized property discovery, AI valuation and a one-tap route to contact an agent.
Read the Full StoryMore Success Stories
E-commerce and retail
+32%conversion ratePersonalized shopping experience for a US fashion retailer
A fast-growing US fashion and lifestyle retailer had plenty of traffic but a 2.1% conversion rate. We combined a recommendation engine with a simpler path from discovery to checkout.
Real estate
90%pricing accuracyTransparent AI property valuation for a multi-city marketplace
A growing real estate marketplace wanted buyers to trust its prices. We built a valuation engine and property pages that compare the estimated value with the asking price.
Resources
Featured Resources
Industry trends and practical guidance to help you get more value from data, AI and technology.
FSMA 204 After the Delay: Using Shipment Monitoring to Get Traceability-Ready by 2028
The FDA Food Traceability Rule deadline moved to July 2028, but the data work is large. Here is how to use shipment monitoring and event data to get ready without wasting the extra time.
CSRD After the Omnibus: What the Revised ESRS Mean for Reporting From 2027
The Omnibus and the simplified ESRS reshaped EU sustainability reporting in 2026. Here is who is in scope, what changed in the standards and how to adapt your data and process.
OpenTelemetry in 2026: Building a Vendor-Neutral Observability Strategy
OpenTelemetry has become the default way to collect telemetry. Here is what changed in 2026 and a practical roadmap for a vendor-neutral observability stack.
Build Golden Records Your Teams Can Trust
Tell us which master data domain causes the most friction today. We will reply within 24 hours and arrange a free consultation to discuss scope and options.
Master Data Management FAQ
Which MDM implementation style should we choose?
Registry style links records across systems without changing them and is the least disruptive. Consolidation builds golden records for analytics and reporting. Coexistence also synchronizes golden records back to source systems, while centralized style makes the hub the system of entry. Many organizations start with consolidation for quick analytical value and evolve toward coexistence. We recommend a style after assessing your systems, latency requirements and how ready the business is to change processes.
Which data domain should we master first?
Choose the domain where fragmentation causes the most measurable pain and where you have committed business ownership. For many companies that is customer data, because it affects marketing, sales, service and finance. For manufacturers and distributors, product or supplier data may deliver faster returns. We evaluate value, data condition and organizational readiness for each candidate and recommend a first domain that can demonstrate results within a reasonable time.
How accurate is automated matching?
Accuracy depends on data quality, available attributes and how carefully rules are tuned. We combine deterministic rules on reliable identifiers with probabilistic or machine-learning matching on names, addresses and other fields, then measure precision and recall on labeled samples. Records in a gray zone go to a steward review queue rather than being merged automatically. Unmerge capability and full history ensure mistakes can be corrected safely.
What drives the cost of an MDM program?
Key cost drivers include platform licensing, the number of domains and source systems, data condition, the chosen implementation style, integration complexity and the size of the stewardship team. Registry or consolidation styles for one domain are significantly less effort than a centralized multi-domain hub. We provide a phased estimate after discovery and look for ways to reuse your existing platforms, including cloud-native approaches on Databricks or Snowflake.
How long does an MDM implementation take?
A first domain in consolidation style can often reach production within a few months, depending on the number of sources and data quality. Coexistence or centralized implementations that change operational processes take longer because they require integration and change management. We structure delivery so that early releases, such as a deduplicated customer list for analytics, provide value while more complex synchronization is built.
How do you keep master data clean after go-live?
We put stewardship in place before go-live, with named owners, review queues, quality dashboards and service levels for resolving issues. Validation at the point of entry and duplicate checks during creation prevent new problems. Match quality and duplicate rates are monitored continuously, and rules are reviewed as the business changes. We can also run MDM operations as a managed service with weekly reporting.