In my previous blog, Data Is a Resource, I argued that data behaves less like a static asset and more like a raw resource. Assets are owned, assigned a value, and sit on a balance sheet. Data does none of those things on its own. It must be managed, refined, and transformed before it creates value.
Data only becomes valuable once it is shaped into something people can actually use.
If we accept data as a resource, we acknowledge that data has value, and the real question is how to turn an organisation’s data resource into valuable business products.
This is where the idea of a pipeline enters the picture – not as technology or tooling, but as a conceptual model for how data is processed, combined, and shaped into information designed for use. Architecture and transformation matter here, but only insofar as they support that outcome. This is not a discussion about data quality; Declan Moore has already explored that comprehensively in Data Is a Liability. Filtering and stabilisation are simply part of making information usable, not perfect.
From Sugar Cane to Product
A sugar refinery provides a useful way to think about this transformation.
Sugar cane arrives in its natural form. It has potential but limited direct use. Value appears only once it is crushed, clarified, concentrated, and packaged. From the same raw input, the refinery produces multiple outputs – raw sugar, refined sugar, syrup, molasses – each designed for a specific purpose and consumer.
Data works the same way. From a single data resource, organisations create multiple information products: dashboards, reports, curated views, analytical datasets, and application screens. The greatest value comes when the data resource is intentionally refined into products designed for consumption.
Data Exists – Products Are Designed
Most organisations already have plenty of data. What they often lack are deliberately designed information products.
When transformation logic exists only within individual reports, spreadsheets, or dashboards, knowledge becomes tacit and fragile. Logic is rebuilt repeatedly. Definitions drift. Trust erodes. When people leave, understanding leaves with them.
An information product is different.
It is a curated, reusable representation of data, created for a specific business purpose and designed to be consumed with confidence. Dashboards, reports, curated views, and analytical datasets all qualify. What matters is not the format, but the intent and design behind them.
Like any piece of industrial equipment, data products without documentation and ownership depreciate quickly. Expecting consistent outcomes without shared understanding is like handing someone a clarifier without an operating manual and assuming they will trust the output.
Golden Syrup: When Central Refinement Is Required
As organisations grow, complexity increases. Business processes span multiple systems. Definitions diverge. Mergers, acquisitions, and operational change introduce inconsistency.
When business and technical turbulence increases, local refinement becomes harder to sustain. Central refinement becomes necessary – not because it is fashionable, but because it provides a place where data can be consistently mixed, stabilised, and shaped into reusable products.
Using the familiar bronze, silver, and gold framing, the gold layer is often misunderstood. Gold is not simply the final technical step or the prettiest table. Golden Syrup represents curated data designed explicitly for consumption.
Golden Syrup is centrally refined, consistently defined, governed for trust, and designed to be reused across multiple products. It exists to provide a stable, shared representation of key business concepts – the kind that many teams rely on, but few should redefine independently.
Where Products Are Created
Source systems, data warehouses, lakes, and analytics platforms are all containers for the data resource. Information products can be created in any of them.
The assumption that all data must pass through a central warehouse before it becomes useful is misleading. In many cases, lightly refined products created close to the source are entirely appropriate. Operational reports, SaaS dashboards, and application screens are all information products – curated and owned, even when that curation is provided by a vendor.
Central platforms matter most when reuse, consistency, and shared understanding are required.
The Takeaway
Treating data as a resource is the mindset.
Designing information as a product is how that mindset is put into practice.
Data does not create value by existing, nor by being stored in increasingly sophisticated platforms. The greatest value appears when data is deliberately refined into products that help the business decide, act, and grow – and when those products are designed to be trusted, reused, and understood.
That is how raw data becomes something the business can actually use.
Alexandra Wiebe
Data Management Consultant,
CDMP Associate
