The IT Law Wiki


Data-at-rest (DAR) is

all data stored on hard drives, thumb drives, digital video disks, compact disks, floppy diskettes, and other similar storage media.[1]
data temporarily or permanently stored in any way, including but not limited to physical drives and non-volatile or volatile memory.[2]

Data-at-rest (DAR) is "data at the end-points of the transmission."[3]


Typical characteristics of data at rest that are notably different in the era of Big Data are volume and variety. Volume is the characteristic of data at rest that is most associated with Big Data. Estimates show that the amount of data in the world doubles every two years. Should this trend continue, by 2020 there would be 500 times the amount of data as existed in 2011. The data volumes have stimulated new ways for scalable storage across a collection of horizontally coupled resources.

The second characteristic of data at rest is the increasing need to use a variety of data, meaning the data represents a number of data domains and a number of data types. Traditionally, a variety of data was handled through transformations or pre-analytics to extract features that would allow integration with other data. The wider range of data formats, logical models, timescales, and semantics, which is desirous to use in analytics, complicates the integration of the variety of data. For example, data to be integrated could be text from social networks, image data, or a raw feed directly from a sensor source. To deal with a wider range of data formats, a federated database model was designed as a database across the underlying databases. Data to be integrated for analytics could now be of such volume that it cannot be moved to integrate, or it may be that some of the data is not under control of the organization creating the data system. In either case, the variety of Big Data forces a range of new Big Data engineering solutions to efficiently and automatically integrate data that is stored across multiple repositories, in multiple formats, and in multiple logical data models.


"Data on a drive may be encrypted by putting the file into an encrypted container (e.g., a file folder) so that only the files in that container are encrypted while the rest of the drive is in plaintext. Or, the entire drive may be encrypted, known as full-disk encryption, so that all the data on the drive is encrypted (e.g., encrypting the user-accessible space on a cell phone so that the contents of that cell phone are encrypted)."[4]