Veritas Technologies LLC

Henry Aloysius

Ashwin Kumar Kayyoor

Scott Douglas Kaiser

Bashyam Tca

Kushal B Shah

Jagadamba Rangaiah

Karthik Rajamony

Bashyam Anant

Mikhail Tarasyuk

Stuart Sperling

Meenal Binwade

Ankit Agarwal

A computer-implemented method for clustering data to improve data analytics may include (1) extracting a social graph from a data set of messages, the social graph indicating messages as edges such that nodes of the edges indicate corresponding senders and recipients in sender-recipient relationships, (2) detecting communities of collaborators by identifying clusters of nodes within the social graph, (3) applying the identified clusters of nodes within the social graph to a grouping calculation to group the messages of the data set into groups of messages, and (4) providing, through a computing interface, results of a data analytics operation to an end user based at least in part on applying the identified clusters of nodes within the social graph to the grouping calculation. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for clustering data to improve data analytics

The disclosed computer-implemented method for identifying subject-matter experts may include (i) collecting, by the computing device, a plurality of electronic messages transmitted within an organization, (ii) creating a message graph for the organization, (iii) extracting a plurality of topics from the plurality of electronic messages transmitted within the organization, (iv) annotating the message graph by correlating each topic within the plurality of topics with each edge of the message graph that represents an electronic message related to the topic, and (v) identifying, based on an analysis of the annotated message graph, at least one vertex that represents an expert on at least one topic from the plurality of topics. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for identifying subject-matter experts

Various systems and methods for configuring and performing DR rehearsal operations. One method involves initiating a disaster recovery rehearsal for an application. The method involves generating a snapshot of a first storage element used by the application. The method also involves configuring a second storage element and starting an instance of the application. Starting the instance of the application utilizes the snapshot and the second storage element. Generating the snapshot, configuring the second storage element, and starting the instance of the application are performed in response to initiating the DR rehearsal.

Disaster recovery rehearsals

The disclosed computer-implemented method for determining topics of data artifacts may include (1) extracting at least one initial keyword from a data artifact with an unknown topic, (2) creating a set of keywords by generating a plurality of contextually relevant keywords related to the initial keyword and combining the initial keyword with the contextually relevant keywords to form the set of keywords, (3) retrieving, from a topic processor, at least one list of topics associated with each keyword within the set of keywords, and (4) generating, based on the retrieved topic lists, an ordered list of probable topics of the data artifact. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for determining topics of data artifacts

The disclosed computer-implemented method for applying content-based retention policies to data artifacts may include (1) identifying one or more features of a data artifact detected on a computing system, (2) identifying a collection of data artifacts that are (A) stored on at least one storage system and (B) retained in accordance with a set of retention policies, (2) determining, based at least in part on the features, that the data artifact detected on the computing system and at least one data artifact within the collection exceed a certain level of similarity relative to one another, (3) analyzing at least one retention policy of the data artifact within the collection, and then (4) providing a suggestion to apply the retention policy of the data artifact within the collection to the data artifact detected on the computing system. Various other methods, systems, and computer-readable media are also disclosed.

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San Jose, CA, United States of America

Henry Aloysius