Abstract: One example method includes identifying, in a computing system, an aggregate data set that includes both data used by a first user and data used by a second user, examining file metadata associated with the data in the aggregate data set and, based on the examination of the file metadata, determining whether or not any data in the aggregate data set is shared by the first and second users. When a determination is made that some data in the data set is shared by the first and second users, the method includes further determining how much of the data is shared, assigning a strength of connection between the first user and the second user based on the extent to which the first user and second user share data and, based on the strength of connection, taking an action to improve operation and/or configuration of the computing system.

Abstract: A data protection ecosystem-based data valuation methodology includes the following steps. One or more of backup data, metadata, and analytics results maintained by a data protection ecosystem are accessed. The backup data, metadata, and analytics results are obtained during the course of the data protection ecosystem providing data backup and recovery functionalities for a data storage environment that stores one or more data sets. A valuation is calculated for at least one of the one or more data sets of the data storage environment based on at least a portion of the accessed backup data, metadata, and analytics results maintained by the data protection ecosystem.

Abstract: One embodiment is related to a method for transferring device information, comprising: receiving, at a second device, device information of a first device with a close proximity communication technique without requiring manual entry of the device information; storing, at the second device, the device information in a digital text and/or numeric format; and transmitting the device information from the second device to the third device without requiring manual entry of the device information.

Abstract: One example method includes identifying, in a computing system, an aggregate data set that includes both data used by a first user and data used by a second user, examining file metadata associated with the data in the aggregate data set and, based on the examination of the file metadata, determining whether or not any data in the aggregate data set is shared by the first and second users. When a determination is made that some data in the data set is shared by the first and second users, the method includes further determining how much of the data is shared, assigning a strength of connection between the first user and the second user based on the extent to which the first user and second user share data and, based on the strength of connection, taking an action to improve operation and/or configuration of the computing system.

Abstract: Combining a Merkle tree with a graph database by defining a Merkle tree with each node having a hashed value of the metadata for the node and any children of that node, associating non-hashed data with the hashed data for each node, wherein the non-hashed data has an up-pointer from a child node to any of its immediate parent node, and defining bi-directional edges between the nodes of the Merkle tree having a graph database structure to create a reference for the up-pointers associated with each Merkle tree node. The bi-directional edges with up-pointers along with the Merkle tree hash scheme allows efficient traversal of the tree where the hash values indicate non-changed nodes to prevent traversing the database, and further allows efficient path definitions by allowing database processes to walk up edges.

Abstract: Embodiments are described for presenting a backed up data object to a client, in a native file format, in response to a request from the client to retrieve the requested data object. The request includes security attributes of the requested data object. If the security attributes in the request match the security attributes stored with the backed up data object, then the requested data objet is returned to the requesting client. When a backup is performed, metadata associated with each backed up data object is stored in the backup data set. When a request is received to restore a backed up data object, a metadata tree is constructed that represents the directory structure of the backed up data objects, and further includes security attributes for each data object and an offset into the backup data set where the requested data object can be found.

Abstract: A set of pages including a set of entries are stored on disk. A set of page headers are stored in memory. Each page header corresponds to a page on disk. A page header includes a page number identifying a corresponding page on disk, a first guide word, and a second guide word. The first and second guide words define minimum and maximum name values, respectively, of entries on the page. Upon a request to determine if an entry associated with a name value exists, the page headers are scanned to identify a page number in a header where the name value is between the guide words. The page, if not resident in memory, is located on disk, loaded into memory, and examined to determine whether the entry exists on the page.

Abstract: Views of files in an archival data storage system are generated by a backup view generator. A storage application generates and stores archival data in an archive system, the archival data corresponding to client data stored on a server or in memory associated with one or more client nodes. The storage application also generates backup files of the archival data which may be stored in a local memory. A set of metadata attributes are associated with each of the backup files. The backup views are generated by comparing metadata values in a view definition file to the sets of attributes associated with the backup files. Generated backup views can be exported for processing, including searching the backup views or displaying the backup views in a user interface.

Abstract: Embodiments for a method of interfacing with a remote application programming interface (API) by defining an execution plan using an interface definition language and a dependency configuration file to generate a constrained directed graph of hierarchically dependent functions of the API, and executing the execution plan using an executing engine that traverses the graph to call the API functions in a defined order and convert data output by a parent function call to input required by a child function call until a terminal vertex is reached that results in directing the resulting in an action such as data to persist and/or affecting the state of a system.

Abstract: This disclosure is describes a system and method for organizing and storing backup data by inode number. Data objects on a file system may be streamed to a backup client that identifies the inode numbers for each streamed data object before streaming the objects to storage. The inode numbers are parsed to create one or more inode directories that can be browsed during a recovery process. In this fashion, the file system can be quickly backed up without requiring the backup client to determine the file system's directory hierarchy.

Abstract: A priority restore agent in a data storage system generates a priority restore data set for a client computer system or device by identifying a set of active data sets and/or a set of key data sets within client system data generated by the client computer system. The priority restore agent looks at or processes file system attributes for the client system data and compares these attributes with predefined restore parameters. The restore parameters may indicate that any file that has been accessed, modified, or created within a particular period of time be included in the priority restore data set. The key data sets may be identified in a set of automated restore rules. A data protection application within the data storage system can restore data in the priority restore data set onto the client computer system after a disaster or system crash.

Abstract: A backup is performed by a client at a time when a backup server is unable to process the backup. The client maintains a cache including a root tag vector and hash entries. The client begins a backup by writing the root tag vector to a journal file and breaking files into pieces. For each piece, the client performs a hash and compares the resulting hash to entries in the cache. If the hash does not match any entries, the client records a request in the journal file to add the corresponding piece of data to an archive. After completing the backup, the journal file can be sent to the server. Before processing the journal file, the server validates the root tag vector. If the root tag vector is valid, the server processes each of the requests to add data. Otherwise, the server discards the journal file.

Abstract: A priority restore agent in a data storage system generates a priority restore data set for a client computer system or device by identifying a set of active data sets and/or a set of key data sets within client system data generated by the client computer system. The priority restore agent looks at or processes file system attributes for the client system data and compares these attributes with predefined restore parameters. The restore parameters may indicate that any file that has been accessed, modified, or created within a particular period of time be included in the priority restore data set. The key data sets may be identified in a set of automated restore rules. A data protection application within the data storage system can restore data in the priority restore data set onto the client computer system after a disaster or system crash.