“Shadow processing” typically refers to a situation in information technology and data management where certain data processing or computational activities occur in an unauthorized or unmonitored manner, often outside the control and visibility of an organization’s official systems and procedures. This term can encompass various scenarios, including:
- Unsanctioned IT Activities: It can refer to employees or individuals within an organization using their personal devices or unauthorized software and services to process or manipulate data without proper oversight or security measures.
- Unofficial Workarounds: When employees or teams resort to creating their own workarounds or solutions to address data processing needs that aren’t supported or efficiently handled by official systems or processes.
- Data Shadow IT: This is a subset of shadow processing specific to data management. It involves employees and departments using external data storage, data analytics tools, or data processing platforms without formal approval or knowledge from the organization’s IT or data management teams.
- Parallel Data Processing: In some cases, shadow processing might occur as a parallel operation alongside official data processing. This can happen when individuals or departments create their own data processing pipelines in addition to the ones provided by the organization.
Shadow processing can introduce risks to an organization, including data security vulnerabilities, compliance issues, and inefficiencies in resource allocation. Therefore, it’s important for organizations to have robust policies and procedures in place to detect, manage, and mitigate shadow processing activities and promote transparency and security in data handling.
