Systems and methods for generating, analyzing, and storing data snippets

1. A system comprising:

one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform:

associating one or more snippets associated with an entity with a data object of an enterprise data platform to determine an activity of the entity;

organizing the one or more snippets based on metadata of the one or more snippets, the metadata including at least timestamp data and location data of the one or more snippets, wherein organizing the one or more snippets comprise:

clustering the one or more snippets based on the location data of the one or more snippets;

augmenting the one or more snippets with transactional data associated with the entity based on the timestamp data of the one or more snippets and timestamp data of the transactional data, the transactional data including at least one of commerce transactions, ingress and egress transactions, network login transactions, or geolocations of internet protocol (IP) addresses associated with the entity; and

analyzing the one or more snippets and the transactional data to determine the activity.

2. The system of claim 1 , wherein the one or more snippets are user generated during playback of one or more data files accessible through the enterprise data platform.

3. The system of claim 2 , wherein the metadata associated with the one or more snippets further includes annotation data by the user during the playback of the data files.

4. The system of claim 1 , wherein organizing the one or more snippets based on the metadata comprises:

aligning the one or more snippets based on the timestamp data of the one or more snippets;

constructing a timeline based on the aligned snippets; and

providing the timeline through a user interface associated with the enterprise data platform.

5. The system of claim 1 , wherein the instructions, when executed, cause the system to further perform:

determining locations most visited by the entity based on the clustering.

6. The system of claim 1 , wherein the instructions, when executed, cause the system to further perform:

displaying the one or more snippets on spatial coordinates of a map through a user interface associated with the enterprise data platform;

determining a path the entity traversed in a given time period based on the metadata data of the one or more snippets; and

providing the path on the map through the user interface.

7. The system of claim 6 , wherein determining the path the entity traversed comprises:

identifying locations the entity had visited in the given time period based on the location data of the one or more snippets;

constructing a timeline of the locations the entity had visited in the give time period based on the timestamp data of the one or more snippets and the timestamp data of the transactional data; and

determining the path the entity traversed based on the locations the entity had visited and the timeline of the locations.

8. The system of claim 1 , wherein the entity is at least one of a person, a vehicle, an item, a location, or a thing of interest depicted in the one or more snippets.

9. The system of claim 1 , wherein the one or more snippets are portions of data files corresponding to the entity, wherein the data files include at least one of video feeds, audio clips, or images.

10. The system of claim 1 , wherein the ingress and egress transactions are associated with a badge reader of a location.

11. A computer-implemented method, the method comprising:

associating, by a computing system, one or more snippets associated with an entity with a data object of an enterprise data platform to determine an activity of the entity;

organizing, by the computing system, the one or more snippets based on metadata of the one or more snippets, the metadata including at least timestamp data and location data of the one or more snippets, wherein organizing the one or more snippets comprises:

clustering the one or more snippets based on the location data of the one or more snippets;

augmenting, by the computing system, the one or more snippets with transactional data associated with the entity based on the timestamp data of the one or more snippets and timestamp data of the transactional data, the transactional data including at least one of commerce transactions, ingress and egress transactions, network login transactions, or geolocations of internet protocol (IP) addresses associated with the entity; and

analyzing, by the computing system, the one or more snippets and the transactional data to determine the activity.

12. The computer-implemented method of claim 11 , wherein the one or more snippets are user generated during playback of one or more data files accessible through the enterprise data platform.

13. The computer-implemented method of claim 11 , wherein organizing the one or more snippets based on the metadata comprises:

aligning the one or more snippets based on the timestamp data of the one or more snippets;

constructing a timeline based on the aligned snippets; and

providing the timeline through a user interface associated with the enterprise data platform.

14. The computer-implemented method of claim 11 , further comprising:

determining, by the computing system, locations most visited by the entity based on the clustering.

15. The computer-implemented method of claim 11 , further comprising:

displaying, by the computing system, the one or more snippets on spatial coordinates of a map through a user interface associated with the enterprise data platform;

determining, by the computing system, a path the entity traversed in a given time period based on the metadata data of the one or more snippets; and

providing, by the computing system, the path on the map through the user interface.

16. A non-transitory computer readable medium of a computing system storing instructions that, when executed, cause the computing system to perform:

associating one or more snippets associated with an entity with a data object of an enterprise data platform to determine an activity of the entity;

organizing the one or more snippets based on metadata associated with the one or more snippets, the metadata including at least timestamp data of the one or more snippets, wherein organizing the one or more snippets comprises:

clustering the one or more snippets based on the location data of the one or more snippets;

augmenting the one or more snippets with transactional data associated with the entity based on the timestamp data of the one or more snippets and timestamp data of the transactional data, the transactional data including at least one of commerce transactions, ingress and egress transactions, network login transactions, or geolocations of internet protocol (IP) addresses associated with the entity; and

analyzing the one or more snippets and the transactional data to determine the activity.

17. The non-transitory computer readable medium of claim 16 , wherein the one or more snippets are user generated during playback of one or more data files accessible through the enterprise data platform.

18. The non-transitory computer readable medium of claim 16 , wherein organizing the one or more snippets based on the metadata comprises:

aligning the one or more snippets based on the timestamp data of the one or more snippets;

constructing a timeline based on the aligned snippets; and

providing the timeline through a user interface associated with the enterprise data platform.

19. The non-transitory computer readable medium of claim 16 , wherein the instructions, when executed, cause the computing system to further perform:

determining locations most visited by the entity based on the clustering.

20. The non-transitory computer readable medium of claim 16 , wherein the instructions, when executed, cause the computing system to further perform:

displaying the one or more snippets on spatial coordinates of a map through a user interface associated with the enterprise data platform;

determining a path the entity traversed in a given time period based on the metadata data of the one or more snippets; and

providing the path on the map through the user interface.