Data-intensive technologies
Applications where data volume, velocity, and complexity are the primary engineering challenges.
How the laws define this
Both regulatory sources establish that data-intensive technologies are defined by data volume, velocity, and complexity posing the primary engineering challenge, rather than computational power alone. Each text highlights distributed databases and stream processing as core underlying technologies, pointing to practical deployments in ride-sharing and e-commerce systems. The principal divergence lies in the scope of illustrative examples provided and the explicit contextual framing. The definition from the UK government call for evidence explicitly adds video streaming to its list of exemplars alongside ride-sharing and e-commerce, while also explicitly scoping the concept to applications within its regulatory context. In contrast, the call for evidence on data regulation in the age of AI and other data-intensive technologies text omits video streaming and describes these as technologies generally rather than applications within a specified governmental frame. Organizations can rely on either guidance to identify systems where data scale creates the main operational hurdle.
Synthesised from the 2 statutory definitions below. Each one is quoted in full, with its source.
What it triggers
- In the United Kingdom, the Department for Science, Innovation and Technology's call for evidence on data regulation in the age of AI and other data-intensive technologies seeks input from businesses, researchers, and individuals.source
Definitions (2)
Technologies where the sheer volume, rapid velocity, and intricate complexity of data, rather than just computational power, constitute the main engineering challenge. Examples include distributed databases and stream processing used in services like ride-sharing and e-commerce.
Within the context of this UK government call for evidence, "data-intensive technologies" are defined as applications where the sheer volume, velocity, and complexity of data constitute the primary engineering challenge, rather than computational power alone. This includes technologies like distributed databases and stream processing, exemplified by ride-sharing, video streaming, and e-commerce systems.
Questions and answers
What are data-intensive technologies?
Data-intensive technologies are those where the sheer volume, rapid velocity, and intricate complexity of data, rather than just computational power, constitute the main engineering challenge. Examples include distributed databases and stream processing used in services like ride-sharing and e-commerce.
What is the status of the UK call for evidence on data regulation?
It is a draft policy that is not binding.
Who should respond to the UK data regulation call for evidence?
UK businesses, researchers, and individuals are invited to provide input on how data rules impact AI.