Should You Build or Buy a Master Data Management Solution?

Video Overview:

Could your engineering team build a Master Data Management solution?

In many cases, yes.

Most enterprises already own much of the technology needed to create basic MDM capabilities. Data platforms can process records at scale. Workflow tools can coordinate tasks. Data quality engines can validate fields. AI coding tools can accelerate the creation of matching, merging and transformation logic.

For a narrow domain, a controlled use case or a problem where an approximate result is acceptable, building may be a rational decision.

The real difficulty begins when a matching engine has to become a production-grade MDM operating model.

In this video, CluedIn examines the build-versus-buy decision without pretending that purchasing software is always the right answer. It explores which capabilities are relatively straightforward to create internally, where complexity begins to grow and why the final part of an MDM implementation often contains most of the operational risk and business value.

The discussion covers:

• When building an MDM capability can make sense

• Why basic deterministic matching is relatively easy to create

• How AI-assisted development has changed the economics of internal software projects

• Why Master Data Management involves more than matching and merging

• How survivorship, exceptions and conflicting source records create complexity

• Why inaccurate fuzzy matching can cause serious downstream consequences

• The importance of cleaning and standardising data before continually expanding matching logic

• Why lineage, auditability, attribution, rollback and impact analysis matter

• How business data owners and subject-matter experts participate in stewardship

• What it takes to move an internal prototype into a reliable enterprise service

• When specialist or highly differentiated requirements may justify a custom build

• Why buying an MDM platform is often a decision about focus, risk and long-term ownership

  The central issue is not whether an enterprise has engineers capable of building matching logic.

  It is whether the organisation wants to design, test, govern, operate and continuously maintain an entire MDM platform as its data, systems, regulations and business requirements evolve.