Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

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: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

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: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.

Abstract: A data storage management approach is disclosed that performs backup operations flexibly, based on a dynamic scheme of monitoring block changes occurring in production data. The illustrative system monitors block changes based on certain block-change thresholds and triggers block-level backups of the changed blocks when a threshold is passed. Block changes may be monitored in reference to particular files based on a reverse lookup mechanism. The illustrative system also collects and stores historical information on block changes, which may be used for reporting and predictive analysis.