18 results about "Enterprise storage" patented technology

The invention discloses an AI Agent-assisted enterprise data analysis method and system, and relates to the technical field of data analysis, and the method comprises the steps: connecting an enterprise network switch, deploying an RS-485 management network, and deploying at least two AI Agent computing nodes at the edge side of the enterprise network switch; carrying out storage redundancy analysis to obtain a redundancy label matrix; establishing a distribution relationship; issuing a redundancy processing task according to the distribution relationship, and performing data processing to obtain a plurality of return data sets; and performing overlay storage on a metadatabase of the enterprise storage management center according to the plurality of return data sets. The technical problems that in the prior art, storage redundancy of an enterprise meta-database is difficult to recognize accurately, storage optimization after data processing is insufficient, and consequently enterprise data storage efficiency is low are solved, efficient redundancy processing and optimized storage of the meta-database of the enterprise storage management center are achieved, and the enterprise data storage efficiency is improved. And the technical effect of enterprise data storage efficiency is improved.

The invention discloses an enterprise information data retrieval system, which belongs to the technical field of information data retrieval, and comprises a data storage module, a data retrieval module, a permission endowing module, an index guide module and an associated data supplement module, the data storage module is used for respectively establishing enterprise storage databases for storing enterprise related data, the data retrieval module comprises a retrieval algorithm and is used for quickly retrieving the data in the data storage module according to information input by a user, and the authority endowing module. According to the enterprise information data retrieval system, the functions of information retrieval, keyword extraction, data compression, integrated data storage, authority control, index optimization and external data supplementation can be achieved, a comprehensive, efficient and safe information retrieval platform is provided for an enterprise, employees inside the enterprise can quickly retrieve information conveniently, and the enterprise efficiency is improved. And the response speed of information retrieval is improved.

The invention provides a snapshot data statistical method, device and equipment and a readable storage medium, and the method comprises the steps: responding to an event generated by a snapshot volume, and recording state information corresponding to the snapshot volume in a snapshot state mapping table according to a snapshot data unit included in the snapshot volume; and in response to the snapshot data statistics signaling, according to the existence state reflected by the state information, obtaining storage capacity information occupied by the corresponding snapshot volume by using a preset algorithm, the preset algorithm comprising accumulating the storage capacity occupied by the data unit of the source data of the corresponding snapshot data unit in the to-be-counted snapshot volume. Through the technical scheme of the specification, the snapshot state mapping table is constructed to track the association relationship of the data units in real time, and accurate measurement of the snapshot capacity is realized based on existence of the state marks, so that the capacity management precision and the operation and maintenance efficiency of a storage system are effectively improved, and the storage cost of an enterprise is reduced.

The invention relates to an enterprise document management system and management method. The enterprise document management system comprises a document management module, a document retrieval module, a workflow management module, an authority management module, a user management module and a statistics and analysis module. The method can help enterprises to effectively manage and utilize the enterprise documents, and aims to provide a centralized, safe and efficient platform to help the enterprises to store, maintain and retrieve various types of documents. Through the system, an enterprise can better manage the life cycle of a document and ensure the security and reliability of the document, and meanwhile, the system aims at improving the cooperation efficiency of a team, promoting the cooperation among team members through the functions of cooperative editing, version control, workflow management and the like, and in addition, improving the efficiency of the team. The enterprise document management system is also dedicated to providing a convenient document access and search function so as to improve the working efficiency and productivity of employees.

The application discloses an enterprise data sharing optimization method based on a local area network and relates to the technical field of data transmission; cross-enterprise distribution information and enterprise internal distribution information are acquired, and cross-enterprise storage networks and enterprise internal storage networks are constructed, respectively; enterprise internal storage and cross-enterprise storage are performed on enterprise storage data; the storage state of the enterprise storage data is acquired; data repair is performed on the enterprise storage data by using the cross-enterprise storage networks; the sharing request of a user is acquired, and the request type is judged; for enterprise internal data sharing, enterprise internal sharing receipts are generated for the user; enterprise internal data sharing is performed by using the enterprise internal sharing receipts; for cross-enterprise data sharing, cross-enterprise sharing receipts are generated for the user; and cross-enterprise data sharing is performed by using the cross-enterprise sharing receipts; and the technical scheme has the advantages that the efficiency of cross-enterprise data sharing and the security of internal data sharing are improved.

The present invention relates to a method for identifying storage buckets, belonging to the technical field of cloud storage. The method includes: S1, collecting enterprise name information, and obtaining enterprise domain name information based on the enterprise name information according to a preset data acquisition method; S2, performing information crawling based on the enterprise domain name information to obtain the web page content within the corresponding domain name; S3, parsing the page content to obtain a page content parsing result, and determining the storage bucket address based on the page content parsing result; S4, screening the storage bucket address based on a preset screening rule to generate a final storage bucket address set. The storage bucket identification method described in the present invention solves the problem of insufficient enterprise storage bucket identification ability, and can help an enterprise discover as many storage bucket addresses related to it as possible, providing a comprehensive data source for subsequent sensitive data identification.

The invention discloses a cross-platform document data management method and device. The cross-platform document data management method comprises the following steps: acquiring a multi-source document data set; obtaining a document multi-dimensional feature matrix corresponding to each piece of document information according to each piece of document information; each piece of document information is clustered according to the document multi-dimensional feature matrix corresponding to each piece of document information, so that a clustered document data set is obtained, and the clustered document data set comprises a classification center, a category cohesion report and a document service category label; generating an optimal storage allocation scheme according to the clustered document data set and enterprise storage resource constraints; and generating a dynamically evolved fractional Brown association network according to the optimal storage allocation scheme. According to the method, long-memory cost dependence among documents is captured through a fractional Brownian motion (FBM) model, and long-term linkage features are quantified through Hurst index correlation, so that the problem of short visibility caused by the fact that traditional correlation analysis only depends on short-term reference or co-occurrence data is solved.

The utility model provides a corrugated carton convenient to assemble, and relates to the technical field of corrugated cartons. Comprising an assembling mechanism, a fixing mechanism is arranged at the top of the assembling mechanism, the assembling mechanism comprises a bottom cover, a placing groove is formed in the top of the bottom cover, two sets of embedding grooves are formed in the inner surface wall of the bottom cover, a box body is movably inserted into the inner surface wall of the placing groove, and two sets of embedding blocks are fixedly connected to the outer surface wall of the box body; and the outer surface walls of the two sets of embedding blocks are movably inserted into the two sets of embedding grooves, and two sets of clamping grooves are formed in the outer surface wall of the box body. According to the corrugated carton assembling mechanism, under the interaction of all the assemblies of the assembling mechanism, the assembling efficiency of the corrugated carton is greatly improved, the packaging operation time is effectively shortened, meanwhile, the overall strength and deformation resistance of the carton body are remarkably improved through the multi-point tenon-and-mortise structure, the structural stability in the transportation process is guaranteed, and in addition, in the non-use state, the assembling efficiency of the corrugated carton is greatly improved. The box body and the bottom cover can be conveniently separated, the storage space occupancy rate is remarkably reduced, and the enterprise storage cost is effectively controlled.

The technology described herein is directed towards mapping the storage tiers of various multi-cloud vendors to an enterprise's storage tiers and the enterprise's associated storage tier datasets, based on enterprise storage tiering definition data. Once mapped, the storage tier datasets are populated based on the vendor's per-tier metadata that are associated with the enterprise's data stored on that vendor's storage tiers. Similar mapping is performed for each other vendor's storage tiers. Once the storage tier datasets are populated based on the corresponding metadata, the metadata's variable parameters (e.g., performance metrics) for the enterprise's stored data can be presented according to the enterprise's own defined tiers and labels for the parameters. The metadata information in the datasets can be viewed per vendor and per enterprise-defined tier dataset, such as for object storage monitoring, cost comparison among different vendors' tiers, and closest vendor-to-enterprise parity comparisons of like variables.

An example method for dynamic data relocation using cloud based ranks comprises monitoring accesses to data stored on a plurality of local ranks of an enterprise storage system; identifying data which has not been accessed for a predetermined amount of time based on the monitored accesses; and moving the data which has not been accessed for the predetermined amount of time to one or more cloud based ranks of the enterprise storage system, wherein each cloud based rank comprises storage space on one or more cloud storage devices, the storage space on the one or more cloud storage devices mapped to corresponding virtual local addresses that are grouped as a virtual local rank.

This invention discloses a method for managing encrypted write anomalies in enterprise-level storage systems. During the data write process, based on the security requirements of the data and the operational status of the storage unit, a corresponding encryption strategy is dynamically selected. During the encrypted write process, reversible encryption markers or failure markers are established for data blocks. When a data block is written but has not reached stable write conditions, its encryption and write phase states are recorded using reversible encryption markers. In subsequent management operations, the process is rolled back to the previous stable point, reconfirming the correspondence between the encryption strategy and the key version without changing the original encrypted content. When a data block write fails, re-encryption and cross-storage unit compensation write processing are triggered using failure markers. By performing distinct management operations based on different markers, this invention can effectively reduce the impact of write anomalies on system stability and performance while ensuring data security.

The application relates to the field of big data, and discloses a big data analysis processing method, device, equipment and medium, which comprises the following steps: acquiring time slices of label data in an enterprise storage big disk constructed based on a preset algorithm; based on the time slices, determining storage media for storing the label data according to a preset cold and hot backup data storage mode; calling the label data in the storage media based on a preset label preloading mechanism; and performing data analysis on the label data to acquire target customer group data. The enterprise storage big disk and the label data for storing data are compressed and converted through the preset algorithm, the storage space for storing data is saved, the efficiency of system query is improved through the cold and hot backup data and the preset label preloading mechanism, and the label and the label value are dynamically increased, so that the current real-time growth data, such as big data analysis processing requirements under the condition of 100 million data, are solved.

The embodiment of the application discloses a kind of energy storage power compensation method and system, the method comprises: according to the historical power consumption data of target enterprise, the peak time power consumption ratio of target enterprise in peak season is estimated, the daily average peak time power consumption of target enterprise in a year and the target enterprise storage capacity are determined;According to the peak time power consumption ratio of target enterprise in peak season and the daily average peak time power consumption of target enterprise in a year, the peak time power consumption of target enterprise reserved in peak season is determined;According to the peak time power consumption of target enterprise reserved in peak season and the target enterprise storage capacity, the power consumption gap of target enterprise in today's second peak time is determined;According to the power consumption gap of target enterprise in today's second peak time, the target enterprise storage capacity, the valley power consumption of target enterprise in today's first peak time is determined, the target enterprise today's flat section charging capacity is determined;Based on target enterprise today's flat section charging capacity, charge is carried out in the flat section time period between today's peak time. By using the time difference of various electricity prices, more comprehensive energy storage cost reduction than traditional peak clipping and valley filling is realized.

The invention discloses an enterprise data sharing optimization method based on a local area network, and relates to the technical field of data transmission. The method comprises the following steps: acquiring cross-enterprise distribution information and intra-enterprise distribution information, respectively constructing a cross-enterprise storage network and an intra-enterprise storage network, respectively performing intra-enterprise storage and cross-enterprise storage on enterprise storage data, acquiring a storage state of the enterprise storage data, and performing data restoration on the enterprise storage data by using the cross-enterprise storage network. The method comprises the following steps: acquiring a sharing request of a user, judging a request type of the sharing request, performing intra-enterprise data sharing by aiming at intra-enterprise data sharing, generating an intra-enterprise sharing receipt for the user, performing intra-enterprise data sharing by utilizing the intra-enterprise sharing receipt, performing cross-enterprise data sharing by aiming at cross-enterprise data sharing, generating a cross-enterprise sharing receipt for the user, and performing cross-enterprise data sharing by utilizing the cross-enterprise sharing receipt; through the technical scheme of the invention, the cross-enterprise data sharing efficiency and the internal data sharing security can be improved.

The invention provides a storage system data management method, device and equipment and a readable storage medium, and the method comprises the steps that the redundancy of a storage system is obtained, the redundancy is related to the number of data hard disks and the number of verification hard disks which are currently configured to the storage system, and a plurality of hard disks are configured as standby hard disks of the storage system according to the redundancy; responding to a hard disk fault event, calling a corresponding number of standby hard disks to store data which should be written into the fault hard disk after the fault occurs; and in response to a failure recovery event of the failed hard disk, reading the data stored during the failure from the corresponding standby hard disk and writing the data into the failure recovered hard disk. Through the technical scheme of the invention, the problems of redundancy reduction and data loss caused by hard disk faults in the prior art are effectively solved, the balance of high reliability of data storage and efficient utilization of a storage space is realized, the storage cost of an enterprise is reduced, and the overall performance of a storage system and the data security are improved.

The technology described herein is directed towards mapping the storage tiers of various multi-cloud vendors to an enterprise's storage tiers and the enterprise's associated storage tier datasets, based on enterprise storage tiering definition data. Once mapped, the storage tier datasets are populated based on the vendor's per-tier metadata that are associated with the enterprise's data stored on that vendor's storage tiers. Similar mapping is performed for each other vendor's storage tiers. Once the storage tier datasets are populated based on the corresponding metadata, the metadata's variable parameters (e.g., performance metrics) for the enterprise's stored data can be presented according to the enterprise's own defined tiers and labels for the parameters. The metadata information in the datasets can be viewed per vendor and per enterprise-defined tier dataset, such as for object storage monitoring, cost comparison among different vendors' tiers, and closest vendor-to-enterprise parity comparisons of like variables.

The present invention relates to the technical field of data management, and particularly to an automatic reconciliation system for enterprise data and an implementation method thereof. The method includes the following steps: obtaining multi-source enterprise bill data; performing data preprocessing on the multi-source enterprise bill data to generate standard multi-source enterprise bill data; decomposing the enterprise bill addresses of the standard multi-source enterprise bill data to generate bill type classification data; archiving and storing the bill type classification data in a database to generate a normalized enterprise storage data set; performing storage table association on the normalized enterprise storage data set to generate a time-series associated storage table; and performing step-by-step initial bill reconciliation on the time-series associated storage table to generate step-by-step initial bill reconciliation data. The present invention improves the automation level and accuracy of the reconciliation process through systematic data preprocessing, normalized storage, automatic initial verification and correction, intelligent anomaly detection, and rule generation.

The invention relates to a property service trace data processing method and system based on AI and blockchain evidence storage, and relates to the technical field of smart community and property management, and the method comprises the steps: inputting a property service contract to a plurality of pre-training deep learning models, and outputting a structured contract service content recognition result as a service standard; packaging the enterprise evidence record containing the service record and the service standard into a service standard evidence packet, and encrypting to generate a unique digital fingerprint; inputting the unique digital fingerprint of the service standard evidence packet and the attribute of the evidence packet into the block chain, and taking the returned block chain transaction ID as an evidence storage voucher; and in response to the query request, obtaining a corresponding evidence storage record from the block chain network according to the task ID or the block chain transaction ID in the evidence packet attribute. According to the method, whether the actual service is consistent with the contract content can be automatically identified and compared, meanwhile, the tampering resistance of the evidence packet storage evidence is improved, and integrated tracing verification processing is supported.