Kirkpatrick 2011 (†325 Data Visible and Invisible): Yet increasingly, the real wealth of data out there is what is known as "massive passive data," or "data exhaust." It's the personal information corporations collect about what products their customers buy and about how they use digital services. It is the digital trails we leave behind, merely by going about our daily lives. It is the data that powers business, which the World Economic Forum has described as a new asset class. (†298)
Noyes 2016 (†780 ): If big data is "primary" data that relates to the core function of your business, data exhaust is secondary data, or everything else that's created along the way. (†1994)
Noyes 2016 (†780 ): The term "big data" is itself a relative term, boiling down essentially to "anything that's so large that you couldn't manually inspect or work with it record by record." In general, data exhaust tends to be even bigger, primarily because there are few limits on what a company can collect. (†1996)
Noyes 2016 (†780 ): Data exhaust can be enormously useful. In that bank example, for instance, knowing where consumers conduct most of their transactions can help the bank do a better job.
¶ "It's not core to the transaction, but it can still be hugely relevant to servicing customers at a better level. It provides a level of understanding and contextualization to that primary transaction or service that's increasingly desired by customers."
¶ Data exhaust can contain important elements of information that you may not be looking for today but that could prove useful in the future. (†1997)
Richtel 2013 (†785 ): TalentBin, another San Francisco start-up firm, searches the Internet for talented programmers, trawling sites where they gather, collecting “data exhaust,” according to the company Web site, and creating lists of potential hires for employers. Another competitor is RemarkableHire, which assesses a person’s talents by looking at how his or her online contributions are rated by others. (†2004)
Techopedia (†411 s.v. "data exhaust"): the data generated as trails or information byproducts resulting from all digital or online activities. These consist of storable choices, actions and preferences such as log files, cookies, temporary files and even information that is generated for every process or transaction done digitally. This data can be very revealing about an individual, so it is very valuable to researchers and especially to marketers and business entities.
¶ Data exhaust refers to all of the related data generated by digital activities, and this data tells a good story about habits and preferences. Data exhaust consists of virtual trails left behind, similar to the exhaust from a vehicle, a byproduct that reveals the trail it has taken. This data is used to target advertisements to specific demographics and for market research, which tells businesses the online preferences, behaviors and habits of potential customers, giving them insight into how to mold their business into something that the people will consume. This is called behavioral targeting.
¶ In more legitimate science, this can be used to improve digital and online processes based on the behaviors of users. We can look for shortcuts to minimize required actions and find areas to optimize, improve or change outright. Data exhaust is widely used in data mining and big data analytics. (†2611)
WEF 2013 (†322 p. 2): The second category of data is observed data, which is created by an individual’s interactions with technology, even when data provision and collection is not the primary purpose of the interaction. Such data is often referred to as ‘data exhaust’ because it is produced as a by-product of other technology functions. (†297)
Wikipedia (†387 s.v. United Nations Global Pulse): Anonymized data generated through the use of services such as telecommunications, mobile banking, online search, hotline usage, transit, etc. (†1266)
