What is Data as a Service (DaaS) and why it matters
A clear definition of Data as a Service (DaaS): what it includes, how it differs from building your own infrastructure and why more companies adopt it.
Read articleWhat metadata is, what a data catalogue is for, and how they help the business find, understand and trust the available data.

In many companies, the biggest obstacle to using data is not that it is missing, but that nobody knows what exists, where it is or whether it can be trusted. Metadata and the data catalogue solve that often-underestimated problem.
Metadata is "data about data": descriptions of what a data point represents, where it comes from, how it was transformed, who uses it and with what quality. A data catalogue is the organised inventory of those assets.
A good catalogue is what makes self-service possible: an analyst or business owner finds, understands and uses data without a technical intermediary. Without a catalogue, self-service becomes chaos; with it, governed autonomy.
The key is that metadata is captured automatically as data flows, not through manual documentation that ages. Modern platforms extract and update metadata automatically, linking it with lineage and quality.
A catalogue is the map that turns scattered data into something the business can find and trust.
Metadata describes each data point and the catalogue inventories it so the business can find, understand and trust the data — the basis of self-service and governance. It must be captured automatically as data flows, linked with lineage and quality, not documented by hand.
Metadata is the information describing each data point; the catalogue is the organised inventory of that metadata so data can be found and understood.
So the business discovers what data exists, understands its meaning and trusts its quality, enabling self-service and governance.
It should not. The effective way is to capture it automatically as data flows, linked with lineage and quality.
A catalogue lets non-technical users find and understand data without an intermediary, turning self-service from chaos into governed autonomy.
Because they expose the origin, quality and meaning of each data point, so users know whether and how to rely on it.
Modern platforms extract and update metadata automatically as data flows, linking it with lineage and quality indicators.
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