Abstract: The disclosed computer-implemented method for automatically linking data analytics to storage may include (1) identifying a request to provision storage for a data analytics task, (2) collecting information relating to the data analytics task, the information comprising at least one of a data type of the data being used as input for the data analytics task and a characteristic of the data analytics task, (3) using a self-service provisioning tool to automatically compute, based on the collected information, a suggested type and size of data storage for the data analytics task, and (4) automatically provisioning data storage for the data analytics task based on the suggested type and size. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method for building an extract, transform, load pipeline may include (i) identifying a plurality of ETL resources available to a user, (ii) categorizing each of the plurality of ETL resources based on at least one characteristic, (iii) provisioning the plurality of ETL resources for use with containers, (iv) presenting a user environment to the user, the user environment including a plurality of container images corresponding to available ETL resources, (v) receiving, from the user, a selection of at least one container image of the plurality of container images, and (vi) running at least one container from the at least one container image, the at least one container utilizing two or more ETL resources of the plurality of ETL resources. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method for facilitating analytics on remotely stored data sets may include (1) identifying, within a secondary storage system, a secondary copy of a data set duplicated from a primary copy of the data set stored in a primary storage system, (2) generating a set of virtual objects that represent at least a portion of the secondary copy of the data set, (3) exposing the set of virtual objects to a remote analytics engine via a network such that the portion of the secondary copy of the data set appears to be stored locally on the remote analytics engine, and then (4) enabling the remote analytics engine to perform at least one analytics job on the portion of the secondary copy of the data set by way of the set of virtual objects via the network. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method for completing sets of computing tasks may include (i) defining a set of computing tasks to be performed in a specified order, (ii) configuring a set of containers such that each container within the set of containers is configured to perform a task within the set of computing tasks, where each container isolates user space of a deployment system from other software on the deployment system while sharing kernel space with the other software, (iii) receiving a request to initiate the set of computing tasks, and (iv) completing, in response to the request, the set of computing tasks by launching the set of containers in the specified order. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method for performing storage location virtualization may include (i) identifying a volume storage location for an operating-system-level virtualization container that isolates an instance of user space, the volume storage location providing a working space for data accessed during the existence of the operating-system-level virtualization container, (ii) mapping, through an automated driver that performs location virtualization, the volume storage location to multiple distinct source locations outside of the operating-system-level virtualization container, rather than a single source location, and (iii) propagating, through the automated driver, changes to the data within the working space of the volume storage location during the existence of the operating-system-level virtualization container to the respective multiple distinct source locations outside of the operating-system-level virtualization container to preserve the changes.

Abstract: The disclosed computer-implemented method for facilitating analytics on data sets stored in remote monolithic files may include (1) identifying, within a secondary storage system, a secondary copy of a data set duplicated from a primary copy of the data set stored in a primary storage system, (2) generating a set of virtual objects that represent at least a portion of the secondary copy of the data set, (3) exposing the set of virtual objects to a remote analytics engine via a network such that the set of individual data objects appears to be stored locally on the remote analytics engine, and then (4) enabling the remote analytics engine to perform at least one analytics job on the set of individual data objects by way of the set of virtual objects via the network. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Techniques for performing an incremental backup are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for performing an incremental backup comprising retrieving a first identifier from a first portion of a prior backup of a database, backing up a first portion of a snapshot of the database, retrieving, using at least one computer processor, a second portion of the snapshot of the database, determining whether a second identifier of the second portion of the snapshot of the database is greater than the first identifier, and in the event the second identifier is greater than the first identifier, backing up the second portion of the snapshot of the database.

Abstract: A method and apparatus for performing granular restoration from machine images stored on sequential backup media is disclosed. In one embodiment, the method for performing granular restoration from machine images stored on sequential backup media includes processing at least one machine image file to identify at least one database file and at least one data object that is arranged within the at least one database file and generating mapping information regarding the at least one data object within the at least one machine image file, wherein the at least one machine image is to be stored on the sequential backup media.

Abstract: A computer-implemented method for backing up virtual machine data may include (1) identifying a volume of data for a guest system within a virtual machine that may be scheduled for a backup from outside the guest system, (2) identifying, before the backup may be scheduled to occur, a plurality of blocks within the volume of data that have changed since a previous backup of the volume of data, (3) partially performing the backup by copying the plurality of blocks to a backup image and (4) completing the backup from outside the guest system once the backup may be scheduled to occur by copying to the backup image an additional plurality of blocks within the volume of data that have changed since identifying the plurality of blocks. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A computer-implemented method for efficiently backing up data may include (1) identifying a volume scheduled for a backup by a computing system, (2) determining that resource usage of the computing system will fall below a predetermined threshold for a period of time, (3) identifying at least one unit of data in the volume of data to copy to a backup image for the backup during the period of time, (4) in response to determining that the resource usage of the computing system will fall below the predetermined threshold for the period of time, copying the unit of data to the backup image during the period of time, (5) taking the snapshot of the volume, and (6) copying at least one additional unit of data from the snapshot to the backup image to make the backup image consistent with the snapshot. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A computer-implemented method for enabling deduplication of attachment files within a database is described. A database file comprising data blocks of an attachment file positioned intermittently among data blocks of the database file is inspected. A first map may be generated from the inspection of the database file and the attachment file. The data blocks of the database file and the data blocks of the attachment file are identified according to the first map. The data blocks of the database file are written to a database data file. The data blocks of the attachment file are written to an attachment data file. The attachment data file is deduplicated with at least one other data file.

Abstract: Various embodiments of a system and method for providing input/output virtualization for a file are disclosed. The system may include a filter program that intercepts a write request for a particular file and stores change information specifying the data and the write location indicated by the write request. However, the file itself is not modified. The filter program may also intercept a read request referencing the file and determine whether change information representing a write request to write data at the location specified by the read request has been previously stored. If so then the data specified by the change information is returned in response to the read request.

Abstract: Techniques for global single instance indexing for backup data are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for indexing backup data. The method may comprise generating a content hash for an item being backed up. The item may be associated with a resource name and the content hash may be used as an identifier in backup and indexing. The method may further comprise saving an entry for the item in an index database. The entry may comprise a resource list which may comprise the resource name and a reference count associated with the resource name. Moreover, the method may comprise setting a value for the reference count.

Abstract: A method and apparatus for performing granular restoration from machine images stored on sequential backup media is disclosed. In one embodiment, the method for performing granular restoration from machine images stored on sequential backup media includes processing at least one machine image file to identify at least one database file and at least one data object that is arranged within the at least one database file and generating mapping information regarding the at least one data object within the at least one machine image file, wherein the at least one machine image is to be stored on the sequential backup media.

Abstract: Techniques for recovering data from cold images are disclosed. In one particular exemplary embodiment, the techniques may be realized as a computer implemented method for recovering data from cold images comprising searching storage associated with a target recovery device, identifying one or more data structures on the storage, parsing the one or more identified data structures, and recovering one or more portions of the one or more parsed data structures.

Abstract: Techniques for backup error management are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for backup error management comprising receiving a backup job error from a backup job, providing an error indicator and at least one user selectable option, receiving a user input corresponding to the at least one user selectable option, and modifying a backup policy to address the error based at least in part on the received user input.

Abstract: Techniques for virtualizing data are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for virtualizing data comprising identifying source data to be virtualized, intercepting an input/output (i/o) request to the source data, determining whether the input/output request is a read request or a write request, in the event the input/output request is a write request, storing one or more changes contained in the write request, and in the event the input/output request is a read request, determining whether a portion of data requested has been modified and responding to the read request. Responding to the read request may comprise providing stored data in the event a portion of the data requested has been modified, and utilizing source data in the event the data requested is unmodified.