System and method for data classification during file backup

A system for performing backup of electronic data, comprising:

• a hardware processor configured to:
• sample metadata of files on a computer during a predetermined time interval;
• deriving derivative features from attributes of the metadata by:
• analyzing values in the attributes of the metadata;
• and
• encoding the values that were analyzed into encoded values in a particular format for the derivative features;
• predicting file usage dynamics based on a combination of the derivative features and the attributes of the metadata;
• derive, using the file usage dynamics, a model of change of the metadata over time, wherein the model of change is a snapshot of dynamically sampled attributes of the files and reflects a state of the computer over the predetermined time interval;
• predict, based on the model of change, a speed of change in size of files of a particular file type and a change in capacity of the computer subsequent to the predetermined time interval;
• generate an urgency model based on the metadata further indicating (1) how soon a file must be retrieved from backup and (2) conditions on whether to back up the file in low latency storage or high latency storage;
• identify on the computer at least one newly stored file of a first file type;
• select a backup plan for the at least one newly stored file, the backup plan indicating when and where to perform a backup according to a determined urgency of the at least one newly stored file, a predicted speed of change in size of files of the first file type, and the predicted change in capacity of the computer;
• and
• back up the at least one newly stored file to a storage server according to the selected backup plan.

A non-transitory computer-readable medium storing thereon instructions that when executed perform a method for backup of electronic data, the instructions comprising:

• sampling metadata of files on a computer during a predetermined time interval;
• deriving derivative features from attributes of the metadata by:
• analyzing values in the attributes of the metadata;
• and
• encoding the values that were analyzed into encoded values in a particular format for the derivative features;
• predicting file usage dynamics based on a combination of the derivative features and the attributes of the metadata;
• deriving, using the file usage dynamics, a model of change of the metadata over time, wherein the model of change is a snapshot of dynamically sampled attributes of the files and reflects a state of the computer over the predetermined time interval;
• predicting, based on the model of change, a speed of change in size of files of a particular file type and a change in capacity of the computer subsequent to the predetermined time interval;
• generating an urgency model based on the metadata further indicating (1) how soon a file must be retrieved from backup and (2) conditions on whether to back up the file in low latency storage or high latency storage;
• identifying on the computer at least one newly stored file of a first file type;
• selecting a backup plan for the at least one newly stored file, the backup plan indicating when and where to perform a backup according to a determined urgency of the at least one newly stored file, a predicted speed of change in size of files of the first file type, and the predicted change in capacity of the computer;
• and
• backing up the at least one newly stored file to a storage server according to the selected backup plan.