Data as a Product: The New Paradigm

Treating data as a product (DaaP) requires the development of reliable systems that can be shared, reused and deliver value. Let’s understand this concept and the important role open source is playing in its implementation.

- Dr Chinmoy Kumar

Data is often nicknamed 'the new oil' as it requires processing similar to oil extraction before it reaches its useful state. It then becomes the power source for business decisions and product development. The technology behind artificial intelligence, automation, recommendation systems and digital ads relies fundamentally on data.

Data has evolved from being an operational byproduct to a product that companies now actively manage. The Data as a Product (DaaP) approach transforms business data management through open source tools such as Apache Kafka for real-time data streams and Airbyte for data integration.

What does 'Data as a Product' mean?

Data as a Product (DaaP) means treating data like a hardware or a software product. The data is actively managed, maintained and improved to serve end users, just like is done with any product. Data was previously locked away in centralised databases that were only accessible by IT teams, which limited users' ability to locate it. DaaP now puts the user, typically a data analyst, data scientist or developer, at the centre. This makes data more accessible, well-documented and reliable.

Today organisations use service level agreements (SLAs) for data management in the same way as they apply them to digital services. The agreements guarantee that data remains up to date, accurate and readily available. This transformation from static storage to delivering usable assets happens because data now serves multiple teams. Organisations across the board now view data as a product that requires reliability, maintenance and user-centred design.