A data consumer can be any user, application, or system that uses data collected by another system or stored in a data repository.
Within an organization or a company, many systems can be considered data producers as they collect or generate data that is stored to be later used by data consumers. This data can then be used to provide analytics or trigger actions. A data consumer can sometimes merge data from several sources and can, in turn, replicate or transform this data to be passed along to other data consumers. Therefore, In many cases, a particular user is both a data consumer and a data producer.
In data architecture, it is essential to identify dependencies between consumers and producers of data. This identification is made to implement data governance policies, security policies, and monitoring. It is also critical to implement data checks in data engineering pipelines, establish schema expectations from data producers stored in data catalogs, and establish data checks that ensure that the information being processed is consistent with a particular business or operational logic.
Data Stewards, Data Consumers, and Data Owners
In data governance, the role of the data consumer carries with it responsibilities to ensure that the data is trustworthy and secured. These responsibilities focus on how the data is secured, how it will be used, how long it can be retained, and with whom it can be shared. Data stewards manage to control and distribute the data. On the other hand, data owners are responsible for defining the data contents, source, and classification, validating it, and authorizing access.
In this context, the data consumer is any actor that can legitimately access the data with an apparent reason to do so. They can use it to create new data, out of which they become data owners with the proper responsibilities. Data Consumers should ensure the data has business value and clear data quality. They also need to ensure that it is solely used for the purpose for which it was collected.