Why a Data Catalog without a Data Quality platform is no longer enough

You've found the data... but can you trust it?

Today, every company understands the value of a data catalog: without one, finding a reliable source in the ocean of an information system becomes mission impossible. But to believe that a good catalog is enough to produce value is to confuse visibility with reliability.

A Data Catalog tells you what you have and where to find it.
A Data Quality platform tells you what condition it's in, whether you can use it, and how to improve it.

👉 O ne without the other is an incomplete strategy.

Towards an active, governed and trusted catalog

Data catalogs were designed to centralize metadata, document datasets and facilitate their discovery. But all too often, they remain static showcases. Integrating a Data Quality platform enables you to move from a static repository to a dynamic workspace, connected to operational reality.

Here's what this integration transforms in concrete terms:

1. Integrated quality scores for immediate reliability assessment

It's not enough to be able to find a dataset. You also need to know whether it's complete, up-to-date, homogeneous and unduplicated.
Displaying a quality score directly in the catalog enables each business or technical user to quickly judge the relevance of a source.

2. Cleaned data, not just exposed

A catalog can index an invalid source. A DQM platform, on the other hand, detects and corrects: duplicates, inconsistent formats, missing values... The data is not just visible, it becomes usable.

3. Continuous monitoring, integrated into the ecosystem

Quality platforms enable real-time monitoring. By connecting them to the catalog, the latter becomes a living dashboard, capable of alerting you to degradations, critical errors or sudden deviations.

Traceability and governance take on a new dimension

A good data catalog must offer a clear lineage. But when you add a quality layer, you're no longer just tracking sources. We track transformations, corrections and the rules applied. This is what we call enriched traceability, essential for audits, RGPD compliance, or sensitive AI projects.

Knowing the origin of a piece of data is all very well.
Knowing how its quality has evolved is what gives confidence.

From documentation to collaboration

A catalog alone remains a documentary tool. When enriched with quality, it becomes a shared workspace, where users can :

• consult quality metrics in context,
  
  
• provide feedback directly on data,
  
  
• track the history of corrections,
  
  
• propose or adjust rules, even in natural language.
  
  

This approach transforms the relationship with data: we no longer simply search, we improve together.

Concrete benefits for decision-makers

The combination of a Data Catalog and a Data Quality platform is not a luxury. It's what finally makes it possible to scale up, secure AI and BI projects, and involve business units in operational and sustainable governance.

The benefits are direct:

• reduced time to find and validate a reliable source ;
  
  
• fewer downstream errors (reporting, AI, automation);
  
  
• accelerated IT/business collaboration;
  
  
• easier compliance, thanks to dynamic, traceable documentation.
  
  

📅 You've got a catalog, but trust is still lacking?

Would you like to transform your Data Catalog into a true foundation for operational governance?
👉 Book an appointment with a Tale of Data expert
to find out how to combine visibility, quality, traceability and action in a single integrated platform.