Dark data has nothing to do with the dark web, nor with illegal transactions. Dark data is the term for information assets that organizations collect, process, and store during normal business activities, but are generally not used for other purposes.
Much of the information that the organization stores are obscure data. This is because, as useful as the data may be, most of the information we tend to keep is simply a guarantee, since we feel the need to keep it in case it is necessary for the future, despite being aware of that it is completely obsolete data for any other use.
What Are Examples Of Dark Data?
Specific examples of what dark data is can vary from one organization to another, although if they are outdated or unstructured, any of the following could be included in this category :
- Client information
- Log files
- Account info
- Data of former employees
- Financial statements
- Raw data from the survey
- Correspondence in the form of an email
- Notes or presentations
- Old versions of relevant documents
Thus, the data that make up the dark data have to do with:
- Lost transactions: They are any type of operation that is carried out against a computer system and that do not necessarily have to be transactional. They may be related to a web service, a reservation system or a purely transactional system; it can be the requests, answers and searches that are not stored, as is the case of lost sales; or the data resulting from mapping the behaviour of customers and suppliers.
- Internet of Things: It is another scenario where dark data is generated: As the data generated by releasing captive information in machines and control systems would be called, connecting industrial environments with the IT ecosystem, managing information related to devices, taking advantage of metrics to understand operational efficiency or digitize analogue devices.
- It is common for most businesses, as common as wireless networks within an establishment or complimentary WiFi found in various places. From the information collected by these devices, it is possible to monitor the position and movements of people and machinery in physical facilities, evaluate operational performance based on position and movement, improve critical operations or optimize the spatial organization of facilities.
How Can The Dark Data Be Managed?
Although dark data is a relatively new concept, there are already organizations that derive value from that dark data and minimize the risk of storing it. The first step they take is usually to manage and organize their legacy data in order to keep the risks and costs associated with obscure data to a reasonable limit.
From periodic auditing of all databases to defining policies and procedures to dispose of old and unnecessary data, actions can be taken to help achieve good results.
Regarding risk, in addition to configuring data management and auditing process, it is convenient to back up the servers with modern techniques and encrypt the information in as much detail as possible. In this way, it should be possible to stifle most of the risks and costs that are normally associated with dark data.