System and method for data classification during file backup

1. A method for performing backup of electronic data, the method 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.

2. The method of claim 1 , further comprising one or more of:

predicting urgency of the at least one newly stored file on the computer based on the urgency model; and

predicting attributes of the at least one newly stored file on the computer based on the urgency model.

3. The method of claim 2 , wherein the attributes comprise one or more of file type and file size.

4. The method of claim 1 , further comprising one or more of:

predicting, using the model of change and the urgency model, which kinds of files are subjected to particular file operations more often than other kinds of files;

predicting which kinds of files grow in a monotonic manner;

predicting which kinds of files are periodically or un-periodically accessed; and

predicting file operations that cause change in system storage capacity or backup, the change being greater than a predetermined threshold.

5. The method of claim 1 , wherein deriving derivative features further comprises:

bounding the encoded values according to the format; and

deriving derivative the features from the attributes in the metadata according to the encoded values.

6. 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.

7. The system of claim 6 , wherein the hardware processor is further configured to:

predict urgency of the at least one newly stored file on the computer based on the urgency model; and

predict attributes of the at least one newly stored file on the computer based on the urgency model.

8. The system of claim 7 , wherein the attributes comprise one or more of file type and file size.

9. The system of claim 6 , wherein the hardware processor is further configured to perform one or more of:

predict, using the model of change and the urgency model, which kinds of files are subjected to particular file operations more often than other kinds of files;

predict which kinds of files grow in a monotonic manner;

predict which kinds of files are periodically or un-periodically accessed; and

predict file operations that cause change in system storage capacity or backup, the change being greater than a predetermined threshold.

10. The system of claim 6 , wherein the hardware processor is further configured to derive the derivative features by:

bounding the encoded values according to the format; and

deriving derivative the features from the attributes in the metadata according to the encoded values.

11. 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.