Systems and methods for determining data storage insurance policies based on data file and hardware attributes

1. A method for determining data storage insurance policies, the method comprising:

receiving, from a computing device, a plurality of data files for storage and a request to add at least one data storage insurance policy to the plurality of data files for protection against data loss;

for each respective data file of the plurality of data files:

extracting data file attributes comprising information based on at least one of access history, storage at the computing device, and metadata of the respective data file;

determining a data recovery score for the respective data file based on at least one of a uniqueness and a criticality of the respective data file;

determining a hardware score for each of a plurality of performance tiers comprising at least one storage server, based on at least one of an available capacity at each of the plurality of performance tiers and a performance cost for storing the respective data file;

comparing the data recovery score of the respective data file and the hardware score and selecting a data storage insurance policy for the respective data file based at least on the comparison; and

executing the data storage insurance policy.

2. The method of claim 1 , wherein the data recovery score is further based on an importance of the respective data file.

3. The method of claim 2 , wherein the uniqueness is a likelihood of the respective data file being present on a sample computing device, the criticality is a likelihood of a different file on the sample computing device having a dependency on the respective data file, and the importance is a value manually set by a user of the computing device.

4. The method of claim 1 , wherein the hardware score is further based on data recovery scores of data files currently stored at each of the plurality of performance tiers.

5. The method of claim 1 , wherein selecting the data storage insurance policy for the respective data file is further based on a plurality of data recovery rules.

6. The method of claim 1 , wherein storage servers of each of the plurality of performance tiers meet different minimum performance ratings, wherein the minimum performance ratings comprise at least one of: processing speed, memory, storage capacity, data retrieval speed, and network access latency.

7. The method of claim 1 , wherein the data storage insurance policy indicates a redundancy of the respective data file, wherein the redundancy comprises storing the respective data file in multiple storage servers of one of the plurality of performance tiers.

8. The method of claim 1 , wherein the data storage insurance policy indicates a recovery time threshold that is a maximum amount of time needed to recover the respective data file in an event of data loss.

9. The method of claim 1 , wherein the data storage insurance policy indicates a compensation amount provided to the user in an event that the respective data file cannot be recovered due to data loss.

10. The method of claim 1 , wherein comparing the data recovery score of the respective data file and the hardware score further comprises determining whether the data recovery score is greater than the hardware score of a given performance tier of the plurality of performance tiers.

11. The method of claim 10 , further comprising:

in response to determining that the data recovery score is not greater than the hardware score for any performance tier of the plurality of performance tiers, selecting a data storage insurance policy in which the respective data file is not stored in any of the plurality of performance tiers and the user is compensated in an event of data loss.

12. The method of claim 1 , further comprising determining the uniqueness of the respective data file using a machine learning algorithm trained using a dataset that comprises data attributes of sample data files in a plurality of sample computing devices and a count of the plurality of computing devices that include each sample data file.

13. The method of claim 1 , further comprising determining the criticality of the respective data file using a machine learning algorithm trained using a dataset that comprises data attributes of sample data files in a plurality of sample computing devices and a count of files on the plurality of computing devices that depend on each sample data file to be accessed.

14. A system for determining data storage insurance policies, the system comprising:

a hardware processor configured to:

receive, from a computing device, a plurality of data files for storage and a request to add at least one data storage insurance policy to the plurality of data files for protection against data loss;

for each respective data file of the plurality of data files:

extract data file attributes comprising information based on at least one of access history, storage at the computing device, and metadata of the respective data file;

determine a data recovery score for the respective data file based on at least one of a uniqueness and a criticality of the respective data file;

determine a hardware score for each of a plurality of performance tiers comprising at least one storage server, based on at least one of an available capacity at each of the plurality of performance tiers and a performance cost for storing the respective data file;

compare the data recovery score of the respective data file and the hardware score;

select a data storage insurance policy for the respective data file based on at least the comparison; and

execute the data storage insurance policy.

15. The system of claim 14 , wherein the data recovery score is further based on an importance of the respective data file.

16. The system of claim 15 , wherein the uniqueness is a likelihood of the respective data file being present on a sample computing device, the criticality is a likelihood of a different file on the sample computing device having a dependency on the respective data file, and the importance is a value manually set by a user of the computing device.

17. The system of claim 14 , wherein the hardware score is further based on data recovery scores of data files currently stored at each of the plurality of performance tiers.

18. The system of claim 14 , wherein selecting the data storage insurance policy for the respective data file is further based on a plurality of data recovery rules.

19. The system of claim 14 , wherein storage servers of each of the plurality of performance tiers meet different minimum performance ratings, wherein the minimum performance ratings comprise at least one of: processing speed, memory, storage capacity, data retrieval speed, and network access latency.

20. The system of claim 14 , wherein the data storage insurance policy indicates a redundancy of the respective data file, wherein the redundancy comprises storing the respective data file in multiple storage servers of one of the plurality of performance tiers.

21. The system of claim 14 , wherein the data storage insurance policy indicates a recovery time threshold that is a maximum amount of time needed to recover the respective data file in an event of data loss.

22. The system of claim 14 , wherein the data storage insurance policy indicates a compensation amount provided to the user in an event that the respective data file cannot be recovered due to data loss.

23. The system of claim 14 , wherein the hardware processor is configured to compare the data recovery score of the respective data file and the hardware score by determining whether the data recovery score is greater than the hardware score of a given performance tier of the plurality of performance tiers.

24. The system of claim 23 , wherein the hardware processor is further configured to:

in response to determining that the data recovery score is not greater than the hardware score for any performance tier of the plurality of performance tiers, select a data storage insurance policy in which the respective data file is not stored in any of the plurality of performance tiers and data recovery is not attempted in an event of data loss.

25. The system of claim 14 , wherein the hardware processor is further configured to determine the uniqueness of the respective data file using a machine learning algorithm trained using a dataset that comprises data attributes of sample data files in a plurality of sample computing devices and a count of the plurality of computing devices that include each sample data file.

26. The system of claim 14 , wherein the hardware processor is further configured to determine the criticality of the respective data file using a machine learning algorithm trained using a dataset that comprises data attributes of sample data files in a plurality of sample computing devices and a count of files on the plurality of computing devices that depend on each sample data file to be accessed.

27. A non-transitory computer readable medium storing thereon computer executable instructions for determining data storage insurance policies, including instructions for:

receiving, from a computing device, a plurality of data files for storage and a request to add at least one data storage insurance policy to the plurality of data files for protection against data loss;

for each respective data file of the plurality of data files:

extracting data file attributes comprising information based on at least one of access history, storage at the computing device, and metadata of the respective data file;

determining a data recovery score for the respective data file based on at least one of a uniqueness and a criticality of the respective data file;

determining a hardware score for each of a plurality of performance tiers comprising at least one storage server, based on at least one of an available capacity at each of the plurality of performance tiers and a performance cost for storing the respective data file;

comparing the data recovery score of the respective data file and the hardware score and selecting a data storage insurance policy for the respective data file based at least on the comparison; and

executing the data storage insurance policy.