Master data management: one trusted record for every customer, product and supplier

When the same customer exists three times in the CRM, with a different address in the ERP, every report, invoice and AI answer built on that data inherits the confusion. We profile your master data, set quality rules, match and merge duplicates into one trusted record, and keep it in step across your systems, using Ataccama ONE and the integration tools you already run.

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What we cover

What master data isThe records every system depends on
Data qualityStart by measuring what is wrong
Matching and mergingFrom duplicates to one golden record
Keeping systems in stepOne record, kept in step across every system
Stewardship and governanceEvery issue tracked until someone fixes it
TechnologyAtaccama ONE, and the tools you already have

What master data is

The records every system depends on

Master data is the shared information about the things your business deals with: customers, products, suppliers, employees, locations and assets. Transactions come and go, but every order, invoice and shipment points back to these records. When they are wrong or duplicated, the errors spread to every system that uses them.

Master data management (MDM) is the combination of process, rules and technology that keeps one accurate, agreed version of each record and makes it available to every system that needs it.

Data quality

Start by measuring what is wrong

Before changing anything, we profile the data: how many records are incomplete, which fields hold values that break the rules, where codes differ between systems, and how many likely duplicates there are. The profile shows where the problems are and how large they are, and it becomes the baseline progress is measured against.

From it, we write data quality rules with the people who own the data, such as a valid tax ID, a postal address that matches the country, or a product with a unit of measure, and run them on a schedule in Ataccama ONE.

What we do

Profiling of completeness, validity and duplicates
Quality rules agreed with data owners
Scheduled monitoring of every rule
Dashboards of quality over time

Matching and merging

From duplicates to one golden record

Matching finds the records that describe the same customer or product, even when the name is spelled differently or the address is formatted another way. Merging then builds one golden record from the best value of each field, by rules you agree: the most recent address, the tax ID from the finance system, the email from the CRM. Matches the rules are unsure about go to a data steward to confirm, so nothing is merged that should not be.

What we do

Matching rules tuned on your own data
Survivorship rules for every field
Steward review of uncertain matches
A history of every merge

Keeping systems in step

One record, kept in step across every system

A golden record helps only if the systems use it. We connect the master data to your CRM, ERP, e-commerce and finance systems through APIs and workflows, so a new customer or a changed address reaches every system that needs it, and a change that conflicts with the master record is flagged rather than overwritten. For a national food cooperative, our workflow keeps customer records, approvals, order history and profile changes in step across four business systems, and flags anything that needs a person.

What we do

Hub, registry or consolidation design, chosen per domain
Two-way sync through APIs and workflows
Conflicts flagged instead of silently overwritten
Exceptions routed to a named reviewer

Stewardship and governance

Every issue tracked until someone fixes it

Rules find problems; people fix them. We set up stewardship so every failed rule becomes a task for the person who owns that data, with the failed checks listed and a trail from detection to fix. For a state public power authority, we run this on Ataccama ONE: quality rules, monitoring projects and issue tracking, connected to Power Automate so every data issue becomes a tracked task with an audit trail.

Governance sets who owns which data, how a definition changes and who may see what. The same rules then apply to Copilot and AI agents, which should use only data that has passed them.

What we do

Data owners and stewards for each domain
Issue tracking with an audit trail
Notifications to the person who can fix it
Governance that Copilot and agents respect

Technology

Ataccama ONE, and the tools you already have

Most of our data quality and master data work runs on Ataccama ONE, which brings profiling, quality rules, monitoring, matching and stewardship into one platform. We also work with the master data and integration tools you may already own, such as Informatica, Talend and Stibo Systems, and connect them to Power Automate, Azure and your business applications.

Case studies

Master data management in practice

Client names are withheld. We are happy to share details on a call.

All case studies

Ongoing engagement
Issues tracked to fix
Energy & utilities
Data Analytics
Data quality program for a state public power authority
We run data quality work on Ataccama ONE for a public power authority: quality rules, monitoring projects and issue tracking, connected to Power Automate so every data issue becomes a tracked task with an audit trail.
- Data issues tracked from detection to fix
- Ataccama ONE connected to Power Automate
Read the case study →
In delivery
4 systems, 1 record
Food manufacturing
Data Analytics
One customer record across four business systems for a national food cooperative
Wholesale customers sign up in the online store, are approved in the CRM, copied to the ERP and marketed to from a separate platform, and changes made by phone reached none of the others. The workflow keeps customer records, approvals, order history and profile changes in step across all four, and flags anything that needs a person.
- Four systems, one customer record
- Exceptions routed to a named reviewer
Read the case study →

Questions

Common questions

What is the difference between data quality and master data management?

Data quality is about whether data is complete, valid and consistent, and it applies to any data. Master data management uses data quality rules, plus matching, merging and synchronization, to keep one trusted version of your core records. You can start with data quality alone; MDM usually follows once the main problems are measured.

Do we need Ataccama to work with you?

No. We recommend Ataccama ONE where it fits, because it covers quality, matching and stewardship in one platform, but we work with the tools you own, and we can start with a profile of your data before any platform decision.

Which data should we start with?

Usually the domain that causes the most visible trouble, most often customers or products. We profile it, fix the worst problems at the source, and only then add the next domain.

How does master data management help with AI?

AI agents and Copilot answer from the data they can reach, so duplicated customers or wrong product details become wrong answers. Clean, governed master data, with rules that agents respect, is one of the most direct ways to make AI answers accurate.

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