Systems and methods for mapping data fields between flat files and relational databases are disclosed. For example, an operator of a computing system may wish to export select fields from a relational database to a data file. The operator must then manipulate the data file's field header to conform to a defined specification. A computer program may automatically map the fields in that field header to the field names identified in the specification. The program may then rename the fields in the field header to that of the corresponding, specified field names.

One example method includes defining a physical namespace, determining a number of virtual namespaces, virtualizing the physical namespace by defining the virtual namespaces on the physical namespace, and generating a modified lookup key that is a function of a name of one of the virtual namespaces. The modified lookup key may be moved between virtual namespaces without requiring interruption of a backup or restore process, and without requiring an associated file system to be taken offline. Movement of the modified lookup key may be transparent to a user and may permit preservation of scripts that were in place prior to the move.

A system can receive, from user input, request data indicative of a request to create a file with a first filename. The system can, based on the request data, determining a second filename for the file. The system can store an association between the first filename and the second filename. The system can create the file in a file system with the second filename.

In a system for efficiently organizing, storing, and/or accessing project data, and for visualizing project progress, for a specified project, a fractal-based or bioinspired reference structure is selected. A file organization and storage structure is generated based on the reference structure. The reference structure includes tags that can indicate the appropriate storage locations for different types of project-related data based on the nature of the data. To storage a file, the name and/or contents of the file are analyzed and matched with one or more tags, so that the file can be stored at the location identified by the best matching tag.

Embodiments are directed to synchronizing files between client devices utilizing different file systems with different filename restrictions. Generally speaking, a server of a cloud-based storage environment can, upon generation of a file or receiving a file from a first client device, detect any “illegal” characters therein, i.e., characters that are predefined by a file system of a second client device of the environment as being impermissible for use in a filename, and substitute a replacement character for those illegal characters. This replacement character can comprise a character that is permissible by the file system of both the first and second client devices, thereby allowing synchronization and access. Additionally, the server(s) can identify the original filename from the first client device and substitute the replacement characters back to the original filename when the file is being accessed by or synchronized with the first client device.

In some implementations, a system may receive inventory data associated with a data storage system. The inventory data identifies file paths for objects stored in the data storage system. The system may detect patterns in prefixes of the file paths using one or more trained machine learning models. The system may normalize the prefixes of the file paths based on the patterns detected in the prefixes. The system may detect datasets of the objects stored in the data storage system based on the normalized prefixes. The system may compare prefixes associated with the detected datasets with prefixes associated with a set of registered datasets that are registered with a metadata repository. The system may determine, based on comparing the prefixes associated with the detected datasets and the prefixes associated with the set of registered datasets, a respective registration classification for each detected dataset.

The present disclosure relates to systems, methods, and non-transitory computer readable media for clustering media items in a semantic space to generate theme-based folders that organize media items by content theme. In particular, the disclosed systems can access media items that are stored in an original folder structure. The disclosed systems can generate content-based tags for each media item in a collection of media items. Based on the generated tags, the disclosed systems can map the collection of media items to a semantic space and cluster the collection of media items. The disclosed systems determine themes for the clusters based on the generated tags. The disclosed systems can present a media item navigation graphical user interface comprising the collection of media items organized by themes. The disclosed system can present the media item navigation graphical user interface without altering the original folder structure.

In a case where a user adds or deletes a separator to or from an automatically generated file name or the like, it is made possible to automatically generate a file reflecting the presence/absence of a separator at the time of transforming a scanned image of a document of the same kind into a file from next time. In a case where a document similar to a document scanned in the past is scanned, based on results of learning including the presence/absence of a separator, a property for a document scanned this time is generated automatically and presented.

A system and methods for presenting a hybrid cloud cache as a file system. The system implements a set of standard file system command line interfaces that present the objects stored by the hybrid cloud cache to users of the system as if the users were viewing and interacting with a traditional file system. The system provides an interactive shell to the users to view the contents of the hybrid cloud cache. The system may be configured to operate on a live instance as well as on an on-disk structure of the hybrid cloud cache. The system may provide the ability to present partially cached cloud data as a file system via the interactive shell for the purposes of development, support, and troubleshooting.

Automated provision and assignment of meaningful business names for auto discovered Applications and Tiers is disclosed. Properties of members of a virtual computing environment are automatically determined. Performing a tokenization process on text corresponding to the members to obtain information from the text. Utilizing a document generation operation to obtain tokens from the text. Performing a text mining operation on the text to obtain Term Frequency (TF) data, Document Frequency (DF) information, an Inverse Document Frequency (IDF), and TF-IDF data, and utilizing the TF-IDF data to automatically generate and assign a name to the Application/Tiers of said virtual computing environment.