Abstract: Certain embodiments disclosed herein reduce or eliminate a communication bottleneck at the storage manager by reducing communication with the storage manager while maintaining functionality of an information management system. In some implementations, operations performed as part of a backup process may be stored in transaction logs. These transaction logs may include information about a transaction performed between the client computing system and the network storage that hosts the backup of the client computing system. The transaction logs may be provided to a secondary storage system that can be used to form a backup index. The backup index may be used to facilitate accessing the data stored at the network storage. Advantageously, generating the transaction logs and separating the generation of the backup index from the backup process can reduce resource usage during performance of the backup and speed up the backup process while further reducing interaction with the storage manager.

Abstract: Described herein are techniques for better understanding problems arising in an illustrative information management system, such as a data storage management system, and for issuing appropriate alerts and reporting to data management professionals. The illustrative embodiments include a number of features that detect and raise awareness of anomalies in system operations, such as in deduplication pruning operations. Such anomalies can include delays in the processing of archive files to be deleted and/or delays in the generation of the list of archive files to delete. Anomalies are characterized by frequency anomalies and/or by occurrence counts. Utilization is also of interest for certain key system resources, such as deduplication databases, CPU and memory at the storage manager, etc., without limitation.

Abstract: Certain embodiments disclosed herein reduce or eliminate a communication bottleneck at the storage manager by reducing communication with the storage manager while maintaining functionality of an information management system. In some implementations, a client obtains information for enabling a secondary storage job (e.g., a backup or restore) from a storage manager and stores the information (which may be referred to as job metadata) in a local cache. The client may then reuse the job metadata for multiple storage jobs reducing the frequency of communication with the storage manager. When a configuration of the information management system changes, or the availability of resources changes, the storage manager can push updates to the job metadata to the clients. Further, a client can periodically request updated job metadata from the storage manager ensuring that the client does not rely on out-of-date job metadata.

Abstract: An improved information management system is described herein that can use artificial intelligence to classify data files (e.g., emails, documents, audio files, video files, etc.) and/or surface in a user interface the classification assigned to the data files. For example, a lightweight training or a heavyweight training can be employed to train classifiers to classify the data files. Use of artificial intelligence to classify data files may reduce the amount of computing resources that the information management system allocates to the data file review process because an auditor may be able to quickly identify those data files that meet the desired criteria using the classification and only request access to those data files. Thus, the information management system may be able to allocate more computing resources to normal or routine tasks, ensuring that such tasks are completed and/or completed in an appropriate amount of time.

Abstract: According to certain aspects, a system can include a client computing device configured to: in response to user interaction, store an identifier associated with a first tag in association with a first file; and in response to instructions to perform a secondary copy operation, forward the first file, a second file, and the identifier associated with the first tag. The system may also include a secondary storage controller computer(s) configured to: based on a review of the identifier associated with the first tag, identify the first file as having been tagged with the first tag; electronically obtain rules associated with the first tag; perform on the first file at least a first secondary storage operation specified by the rules associated with the first tag; and perform on the second file at least a second secondary storage operation, wherein the first and second secondary storage operations are different.

Abstract: Systems and methods are disclosed for cross-system user-level management of data objects stored in one or more information management systems, and for user-level management of data storage quotas in information management systems, including data objects in secondary storage. An illustrative quota manager is associated with one or more information management systems. The quota manager comprises a quota value representing the maximum amount of data storage allowed for a given end-user's primary and secondary data in the one or more information management systems. The quota manager determines whether data associated with the end-user has exceeded the storage quota, and if so, prompts the end-user to select data for deletion, the deletion to be implemented globally, across the primary and secondary storage subsystems of the respective one or more information management systems. Meanwhile, so long as the quota is exceeded, the quota manager instructs storage managers to block backups of end-user's data.

Abstract: The data storage system according to certain aspects can filter secondary copies of data (e.g., backups, snapshots, archives, etc.) generated by multiple client computing devices into a single, filtered, global reference copy. A reference copy may be a filtered view or representation of secondary storage data in a data storage system. A reference copy may include a data structure that includes references to a subset of secondary storage data that meets certain filtering criteria. The filtering criteria may be specified by users according to user preference. Data included in a reference copy may be stored in native format (e.g., format of the application that generated the data) and be accessible through the application associated with the data.

Abstract: An information management system is provided herein that uses machine learning (ML) to predict what data to store in a secondary storage device and/or when to perform the storage. For example, a client computing device can be initially configured to store data in a secondary storage device according to one or more storage policies. A media agent in the information management system can monitor data usage on the client computing device, using the data usage data to train a data storage ML model. The data storage ML model may be trained such that the model predicts what data to store in a secondary storage device and/or when to perform the storage. The client computing device can then be configured to use the trained data storage ML model in place of the storage polic(ies) to determine which data to store in a secondary storage device and/or when to perform the storage.

Abstract: Systems and methods are disclosed for cross-system user-level management of data objects stored in one or more information management systems, and for user-level management of data storage quotas in information management systems, including data objects in secondary storage. An illustrative quota manager is associated with one or more information management systems. The quota manager comprises a quota value representing the maximum amount of data storage allowed for a given end-user's primary and secondary data in the one or more information management systems. The quota manager determines whether data associated with the end-user has exceeded the storage quota, and if so, prompts the end-user to select data for deletion, the deletion to be implemented globally, across the primary and secondary storage subsystems of the respective one or more information management systems. Meanwhile, so long as the quota is exceeded, the quota manager instructs storage managers to block backups of end-user's data.

Abstract: Certain embodiments described herein relate to an improved disk usage growth prediction system. In some embodiments, one or more components in an information management system can determine usage status data of a given storage device, perform a validation check on the usage status data using multiple prediction models, compare validation results of the multiple prediction models to identify the best performing prediction model, generate a disk usage growth prediction using the identified prediction model, and adjust the available space of the storage device according to the disk usage growth prediction.

Abstract: Disclosed are systems and methods for providing a user-centric interface into an information management system. The interface may enable a user to search for, view, and modify data objects in an information management system that are associated with the user or with the user's username. The interface may also enable a user to apply administrator-like functions to the data objects associated with the user. The administrator-like functions may include content modification, deduplication operations, and storage policy adjustments, among others.

Abstract: Techniques for enabling user search of content stored in a file archive include providing a search interface comprising a search rules portion and an action rules portion, receiving a file archive search criterion comprising at least one search rule, and searching the file archive using the search criterion. The techniques also include generating a set of files filtered using the search criterion and performing an action specified in the action rules portion on a file included in the set of files.

Abstract: The disclosed technology can receive a voice query or text query in a natural language and translate it from natural language to a native database management language to respond to the query. For example, a human can ask his or her computer to “show large emails from December 2016”, and a data agent on computer can receive the voice request, convert audio associated with the voice to words in natural language, convert natural language into a SQL query, and convert the SQL query into a database management query. The data agent is trained with a corpus of technical documents and rules to determine the intent or keywords for answering the query. In some implementations, the disclosed technology can also include a chatbot and/or administrative assistant to enable a human to interface with a database management software using voice or text. In some implementations, the disclosed technology allows the user to automatically connect to a help desk technician to assist in completing the query.

Abstract: The disclosed technology can receive a voice query or text query in a natural language and translate it from natural language to a native database management language to respond to the query. For example, a human can ask his or her computer to “show large emails from December 2016”, and a data agent on computer can receive the voice request, convert audio associated with the voice to words in natural language, convert natural language into a SQL query, and convert the SQL query into a database management query. The data agent is trained with a corpus of technical documents and rules to determine the intent or keywords for answering the query. In some implementations, the disclosed technology can also include a chatbot and/or administrative assistant to enable a human to interface with a database management software using voice or text. In some implementations, the disclosed technology allows the user to automatically connect to a help desk technician to assist in completing the query.

Abstract: The disclosed technology can receive a voice query or text query in a natural language and translate it from natural language to a native database management language to respond to the query. For example, a human can ask his or her computer to “show large emails from December 2016”, and a data agent on computer can receive the voice request, convert audio associated with the voice to words in natural language, convert natural language into a SQL query, and convert the SQL query into a database management query. The data agent is trained with a corpus of technical documents and rules to determine the intent or keywords for answering the query. In some implementations, the disclosed technology can also include a chatbot and/or administrative assistant to enable a human to interface with a database management software using voice or text.

Abstract: Techniques for enabling user search of content stored in a file archive include providing a search interface comprising a search rules portion and an action rules portion, receiving a file archive search criterion comprising at least one search rule, and searching the file archive using the search criterion. The techniques also include generating a set of files filtered using the search criterion and performing an action specified in the action rules portion on a file included in the set of files.

Abstract: Disclosed are systems and methods for providing a user-centric interface into an information management system. The interface may enable a user to search for, view, and modify data objects in an information management system that are associated with the user or with the user's username. The interface may also enable a user to apply administrator-like functions to the data objects associated with the user. The administrator-like functions may include content modification, deduplication operations, and storage policy adjustments, among others.

Abstract: Described herein are techniques for better understanding problems arising in an illustrative information management system, such as a data storage management system, and for issuing appropriate alerts and reporting to data management professionals. The illustrative embodiments include a number of features that detect and raise awareness of anomalies in system operations, such as in deduplication pruning operations. Such anomalies can include delays in the processing of archive files to be deleted and/or delays in the generation of the list of archive files to delete. Anomalies are characterized by frequency anomalies and/or by occurrence counts. Utilization is also of interest for certain key system resources, such as deduplication databases, CPU and memory at the storage manager, etc., without limitation.

Abstract: Systems and methods for storage pruning can enable users to delete, edit, or copy backed up data that matches a pattern. Storage pruning can enable fine-grain deletion or copying of these files from backups stored in secondary storage devices. Systems and methods can also enable editing of metadata associated with backups so that when the backups are restored or browsed, the logical edits to the metadata can then be performed physically on the data to create a custom restore or a custom view. A user may perform operations such as renaming, deleting, modifying flags, and modifying retention policies on backed up items. Although the underlying data in the backup may not change, the view of the backup data when the user browses the backup data can appear to include the user's changes. A restore of the data can cause those changes to be performed on the backup data.

Abstract: Certain embodiments disclosed herein reduce or eliminate a communication bottleneck at the storage manager by reducing communication with the storage manager while maintaining functionality of an information management system. In some implementations, operations performed as part of a backup process may be stored in transaction logs. These transaction logs may include information about a transaction performed between the client computing system and the network storage that hosts the backup of the client computing system. The transaction logs may be provided to a secondary storage system that can be used to form a backup index. The backup index may be used to facilitate accessing the data stored at the network storage. Advantageously, generating the transaction logs and separating the generation of the backup index from the backup process can reduce resource usage during performance of the backup and speed up the backup process while further reducing interaction with the storage manager.