One trusted view across your data.
Unify fragmented records into trusted master data. Resolve duplicates, reconcile conflicting details, and connect shared entities while keeping data ownership and access under your control.
Different records. One real-world entity.
The same customer can appear differently across your CRM, billing, and support systems. MDM connects these records, resolves conflicting details, and establishes one trusted version for every team to use.
Contact: Maya Rao
Address: 12 Park Rd.
Contact: M. Rao
Address: 12 Park Road
Contact: Maya Rao
Address: 8 Lake Street
Connect related records.
Resolve conflicting values.
Master ID: MDM-00128
- Legal name
- ACME Corporation From Billing
- Primary contact
- Maya Rao From CRM
- Registered address
- 12 Park Road From Billing
Linked to all three source records.
Your rules decide which values win. Here, Billing supplies the legal name and registered address, while CRM supplies the primary contact.
Connect shared entities. Keep control of your data.
Identify matching customers, vendors, or students across organizations without pooling raw personal data. Each participant retains its own records, while agreed sharing rules determine which matching results are available to others.
Raw personal data stays within this organization's boundary.
Compare protected inputs under agreed matching rules.
Raw personal data stays within this organization's boundary.
Two local records linked to the same entity.
Only approved match results are shared with authorized participants.
From incoming records to trusted master data.
Match related records, resolve conflicting values, and review uncertain cases before distributing approved master data to the systems that depend on it.
Match
Identify records that refer to the same entity, even when names and formats differ.
Resolve
Apply source priorities and business rules to select the most reliable field values.
Registered address
8 Lake Street 12 Park Road Billing source takes priorityReview
Route uncertain matches and exceptions to a data steward for a decision.
Steward checks source details and confirms the match.
✓ Merge approvedDistribute
Deliver approved master data to connected applications and analytics systems.
Governance across every step. Define who can approve changes, retain source lineage, and keep a history of matching and merge decisions.
FAQs
What is Master Data Management?
Master Data Management (MDM) creates and maintains trusted records for core business entities such as customers, products, vendors, employees, and students. It connects information across sources so teams and systems can work with consistent data.
How is MDM different from data deduplication?
Deduplication identifies and removes duplicate records. MDM goes further by resolving conflicting values, defining data ownership, maintaining source lineage, and keeping master records consistent as information changes.
What is a golden record?
A golden record is the authoritative representation of an entity, built from information across multiple sources. Different fields can come from different systems—for example, a legal name from billing and a contact number from CRM.
How are conflicting values resolved?
Survivorship rules determine which value takes priority based on factors such as source reliability, recency, and completeness. Uncertain cases can be routed to a data steward for review.
Can organizations match records without sharing raw personal data?
Privacy-preserving entity resolution can identify shared entities using protected matching inputs instead of pooling raw personal data. The information disclosed depends on the matching approach and the participants’ agreed access and sharing rules.
Does MDM replace existing CRM or ERP systems?
MDM typically works alongside existing systems. It provides a consistent identity and trusted master values that connected applications can reference or receive through configured integrations
How does master data stay current?
Source changes can be processed through scheduled updates or event-driven pipelines, depending on the implementation. Updated records pass through matching, resolution, and any required review before being distributed.
Turn Raw Data Into Usable Data
Stop spending hours manually extracting and aligning information.
Use Paxcel to extract, standardize, and prepare your data for analytics and AI.