104 results about "Data analyst" patented technology

The present invention generally relates to computer databases and, more particularly, to data mining and knowledge discovery. The invention specifically relates to a method for constructing segmentation-based predictive models, such as decision-tree classifiers, wherein data records are partitioned into a plurality of segments and separate predictive models are constructed for each segment. The present invention contemplates a computerized method for automatically building segmentation-based predictive models that substantially improves upon the modeling capabilities of decision trees and related technologies, and that automatically produces models that are competitive with, if not better than, those produced by data analysts and applied statisticians using traditional, labor-intensive statistical techniques. The invention achieves these properties by performing segmentation and multivariate statistical modeling within each segment simultaneously. Segments are constructed so as to maximize the accuracies of the predictive models within each segment. Simultaneously, the multivariate statistical models within each segment are refined so as to maximize their respective predictive accuracies.

The present invention generally relates to computer databases and, more particularly, to data mining and knowledge discovery. The invention specifically relates to a method for constructing segmentation-based predictive models, such as decision-tree classifiers, wherein data records are partitioned into a plurality of segments and separate predictive models are constructed for each segment. The present invention contemplates a computerized method for automatically building segmentation-based predictive models that substantially improves upon the modeling capabilities of decision trees and related technologies, and that automatically produces models that are competitive with, if not better than, those produced by data analysts and applied statisticians using traditional, labor-intensive statistical techniques. The invention achieves these properties by performing segmentation and multivariate statistical modeling within each segment simultaneously. Segments are constructed so as to maximize the accuracies of the predictive models within each segment. Simultaneously, the multivariate statistical models within each segment are refined so as to maximize their respective predictive accuracies.

A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.

The present invention encompasses a physical or virtual, computational, analysis, fusion and correlation system that can automatically, systematically and independently analyze collected sensor data (upstream) aboard or streaming from aerial vehicles and / or other fixed or mobile single or multi-sensor platforms. The resultant data is fused and presented locally, remotely or at ground stations in near real time, as it is collected from local and / or remote sensors. The invention improves detection and reduces false detections compared to existing systems using portable apparatus or cloud based computation and capabilities designed to reduce the role of the human operator in the review, fusion and analysis of cross modality sensor data collected from ISR (Intelligence, Surveillance and Reconnaissance) aerial vehicles or other fixed and mobile ISR platforms. The invention replaces human sensor data analysts with hardware and software providing two significant advantages over the current manual methods.

A computer system implements a risk model for detecting outliers in a large plurality of transaction data, which can encompass millions or billions of transactions in some instances. The computing system comprises a non-transitory computer readable storage medium storing program instructions for execution by a computer processor in order to cause the computing system to receive first features for an entity in the transaction data, receive second features for a benchmark set, the second features corresponding with the first features, determine an outlier value of the entity based on a Mahalanobis distance from the first features to a benchmark value representing an average for the second features. The output of the risk model can be used to prioritize review by a human data analyst. The data analyst's review of the underlying data can be used to improve the model.

The invention discloses a method for solving the problem of data privacy disclosure in multi-party computation Using a trusted execution environment at the cloud hardware level. In the absence of a trusted third party, Participants who hold the data are able to authenticate remotely the key management program that executes in a trusted execution environment in the cloud, after confirming that theprogram has not been tampered with, the program encrypts its own data with the public key obtained from the program, transmits the data to the cloud, and performs the analysis and calculation of multi-party data in the form of mixed operation based on partial homomorphic encryption technology and hardware-level trusted execution environment at the cloud. The method does not require a centralized authority to complete the computation, so that the data analyst can analyze the data without requiring a third-party trustworthy mechanism, Completing the analysis and calculation of multi-party data can effectively reduce the risk of data privacy leakage in multi-party computation. Compared with the method based on garbled circuit, the method does not need complex key agreement mechanism and has high efficiency.

Systems, methods, and computer products that identify data that is related to and associated with data that has been selected from a multidimensional database. The overwhelming amount of data in a multidimensional database that may be viewed by a user, such as a data analyst, is reduced to the selected and associated data by use of index data and related index data, according to the present invention. The views of selected data and related data may be highlighted and formatted for presentation to the user. Further, irrelevant data is filtered out and not presented to the user. Existing systems have not been able to efficiently and adequately identify data that is related to and associated with selected data in a multidimensional database.

The invention provides a data analysis system and method, a storage medium and electronic equipment, and the system comprises a data collection module which is used for collecting real-time data and offline data, and storing the collected offline data in an HDFS in a Hive form; The real-time calculation module responds to a query instruction of a user, real-time data are consumed through a distributed processing engine Flink to form a real-time data wide table, and data of the real-time data wide table are transferred into a Druid through message middleware kafka; The offline calculation module is used for cleaning and calculating offline data by using Hive to form an offline data width table and synchronizing the offline data width table into a distributed analysis engine Kylin to form amulti-dimensional offline data pre-summary table; And a query engine module. According to the invention, data can be accessed in a real-time or offline manner, and the core model can be abstractly calculated. A data analyst can screen the content to be analyzed by himself / herself in a supporting and pulling manner, and then can display the content in a manner of a rich visual chart.

Systems, methods, and computer products that interpret, explain, and manipulate exceptions in multidimensional data. The present invention assists the data analyst by providing a simplified view of the multidimensional data that enables analysis of the important results of data exception exploration. Further, the preferred embodiment of the present invention incorporates the effect of density of the data along each dimension. The preferred embodiment of the present invention also provides the framework necessary to assign linguistic meaning to the exception for each dimension. This enables data analysis to obtain information about the value of the data that is present.

A method for performing data analytics on outsourced data may include generating, by a data owner, a binary tree representing data from the data owner, where each node of the binary tree is associated with an identity that represents a data element or an interval of data elements, computing, by the data owner, an identity token and encrypting the identity token for each of the identities in the binary tree, generating a range query token using an identity selected by a data analyst and a secret key input by the data owner and computing a decryption key for the selected identity, and analyzing the data, by the data analyst, by comparing the computed decryption key for the selected identity with each of the encrypted identities.

The present invention discloses a data abnormal fluctuation detecting method and apparatus. The method comprises: obtaining to-be-detected data, wherein the to-be-detected data comprises at least one piece of index data; according to a data abnormal fluctuation detecting method, determining at least one piece of abnormal fluctuation index data in the at least one piece of index data; and carrying out analysis on the abnormal fluctuation index data respectively according to corresponding preset dimension information, and generating a corresponding abnormal fluctuation analysis result, the preset dimension information comprises dimensions of the abnormal fluctuation index data, and at least one dimension index data corresponding to each dimension. According to the technical scheme provided by embodiments of the present invention, technical problems in the prior art that abnormal fluctuation detection and analysis time is long, a cost is high and an accuracy rate is low due to a data analyst determining whether each index data in the to-be-detected data occurs abnormal fluctuation and analyzing causes of abnormal fluctuation are solved, and efficiency of abnormal fluctuation detection accuracy and abnormal fluctuation cause analysis is improved.

Privacy-preserving stream analytics (personal data collection method, apparatus, and / or system) from an electronic (e.g., mobile) device providing communications, such as to a network (e.g., Internet). Data queries from a data analyst are received but not directly answered with a truthful query response. Truthful responses are privatized and anonymized based on a randomized response mechanism which releases privatized data and not the original answer. Anonymously transmitting randomized responses from the data owner to data aggregator using shares, each share of which is individually transmitted to an independent aggregator, which is configured for independently and asynchronously process each share, and sharing results with one another to arrive at a query response over an aggregate number of data owners.

The invention relates to a form data privacy protection method fusing a differential privacy GAN model and a PATE model. The method comprises the steps of 1, training a differential privacy generationmodel by using original table data; 2, training a teacher classifier under the differential privacy budget by using the original table data; Step 3, generating 'false' table data by using the generation model, predicting labels of the 'false' table data by using a teacher classifier, selecting data with consistent prediction labels and generated labels, defining an 'available' data set, and training a student classifier by using the 'available' data set; and step 4, releasing the generation model and the student classifier, synthesizing data by using the generation model, selecting the data by using the student model, and finishing a data analysis task. According to the method, privacy protection is carried out on the table data in the data release stage, a data analyst cannot restore original training data through a generation model and cannot speculate the original training data through a student model, protection on the original table data is achieved, and the requirement of the data analyst for the data is met.

Systems, methods, and computer products that rank and explain dimensions associated with exceptions in multidimensional data. The present invention assists the data analyst by providing a simplified view of the multidimensional data that enables analysis of the important results of data exception exploration. Further, the preferred embodiment of the present invention incorporates the effect of weighting factors associated with the importance of the data along with an analysis of the numerical contribution from each dimension. The weighting factors may be based on data mining results or may be obtained from the user. This enables data analysts to obtain information about the value of the data that is presented.

Systems, methods, and computer products that interpret, explain, and manipulate exceptions in multidimensional data. The present invention assists the data analyst by providing a simplified view of the multidimensional data that enables analysis of the important results of data exception exploration. Further, the preferred embodiment of the present invention incorporates the effect of density of the data along each dimension. The preferred embodiment of the present invention also provides the framework necessary to assign linguistic meaning to the exception for each dimension. This enables data analysts to obtain information about the value of the data that is present.

A system is provided including an implantable device configured to be implanted subcutaneously within a patient, a clinician monitoring and control device, an optional patient mobile device, a remote server and / or at least one data analyst device used by a data analyst. The implantable device may communicate with any or all of the monitoring and control device, the mobile device and / or the remote server through the charging device or by establishing a direct wireless connection with each such device. The data analyst device may establish a direct connection with the remote server and also may establish a connection with the monitoring and control device and the mobile device. By analyzing and reviewing the data generated by the implantable device, the data analyst may diagnose a medical condition or indicate a heightened risk of a condition.

In one or more embodiments of the invention, functional data analysts may use a functional data authoring module to capture functional metadata in a consistent manner. Conflict reports for the business processes may be generated for a subset of the business processes or as an overall report across all business processes. One or more embodiments of the invention may provide early detection of data usage and type conflicts from functional data requirements, automated detection of conflicts from functional data requirements, reports listing detected conflicts, conflicts resolution tracking mechanism, ongoing notification regarding changes in functional data requirements or detected conflicts, and avoidance of conflicting functional requirement in the realization phase, thereby reducing costs and project risks and avoiding project delays.

A method and apparatus of processing a customer call is disclosed. The customer call may be initiated for an IVR type system or a live agent. An example method of processing the call may include receiving customer call data and recording the customer call data in a database server. The method may also include performing speech analytics on the recorded customer call data to determine instances of predefined information that occurred during the customer call, and displaying the results of the speech analytics on a user interface. The call analytics may populate a dashboard interface that provides a data analyst with an opportunity to understand the positive and negative portions of the call for future call improvement.

Methods that identify data that is related to and associated with data that has been selected from a multidimensional database. The overwhelming amount of data in a multidimensional database that may be viewed by a user, such as a data analyst, is reduced to the selected and associated data by use of index data and related index data, according to the present invention. The views of selected data and related data may be highlighted and formatted for presentation to the user. Further, irrelevant data is filtered out and not presented to the user. Existing systems have not been able to efficiently and adequately identify data that is related to and associated with selected data in a multidimensional database.

A night vision system includes an image sensor and circuitry coupled to a digital storage medium or transmitter that periodically samples a signal provided by the image sensor and stores the sampled image to be viewed in near real time or at a later date by a data analyst. The night vision system includes an imaging assembly with a casing surrounding an image intensifier and the associated circuitry along with a port for accepting a power and / or signal cable for providing power to the image assembly and image signal data to the digital storage medium. The system may further include a daytime camera and a switch for toggling the image signal data input to the digital storage medium between the daytime camera and the low light image sensor, as well as a transmission system for wirelessly transmitting signals.

The systems and methods described herein provide highly dynamic and interactive data analysis user interfaces which enable data analysts to quickly and efficiently explore large volume data sources. In particular, a data analysis system, such as described herein, may provide features to enable the data analyst to investigate large volumes of data over many different paths of analysis while maintaining detailed and retraceable steps taken by the data analyst over the course of an investigation, as captured via the data analyst's queries and user interaction with the user interfaces provided by the data analysis system. Data analysis paths may involve exploration of high volume data sets, such as Internet proxy data, which may include trillions of rows of data. The data analyst may pursue a data analysis path that involves, among other things, applying filters, joining to other tables in a database, viewing interactive data visualizations, and so on.

The invention discloses a data processing method and device and an electronic device. The method comprises the steps of acquiring target data, acquiring target diagram data sets based on the target data and generating a target diagram corresponding to the target data based on the target diagram data sets. By conducting diagram data set analyzing and acquiring on the target data and then generating the visual diagram corresponding to the target data based on the target diagram data sets, manual data retrieval content and icon setting is not needed in the process, data analysts with abundant data experience do not need to understand principles of visual tools, in this way, the visualization processing operation procedures are reduced, the operation time is saved, and the visualization processing efficiency of the data is obviously improved.

The invention provides an online log analysis method and system and electronic terminal equipment thereof. The method comprises the following steps: S1, conducting log preprocessing on each unanalyzedlog to obtain a plurality of unanalyzed log sequences with different log lengths, and classifying the unanalyzed log sequences into corresponding first log groups; S2, acquiring a log character string of each log sequence in the first log group, calculating the similarity of the log character strings, and performing online clustering based on the similarity of the log character strings; and S3, taking the unanalyzed log sequence as a query item, matching the common node with the template in the template spanning tree of the second log group to obtain the template. The method has the advantages that the logs are classified according to the length, the logs are subjected to secondary clustering based on the log character string similarity, finally, the template spanning tree is used for extracting the log template, the method can efficiently and accurately extract the log template from the unstructured logs, and a data analyst can conveniently carry out higher-level analysis and processing on the logs.

The present invention encompasses a physical or virtual, computational, analysis, fusion and correlation system that can automatically, systematically and independently analyze collected sensor data (upstream) aboard or streaming from aerial vehicles and / or other fixed or mobile single or multi-sensor platforms. The resultant data is fused and presented locally, remotely or at ground stations in near real time, as it is collected from local and / or remote sensors. The invention improves detection and reduces false detections compared to existing systems using portable apparatus or cloud based computation and capabilities designed to reduce the role of the human operator in the review, fusion and analysis of cross modality sensor data collected from ISR (Intelligence, Surveillance and Reconnaissance) aerial vehicles or other fixed and mobile ISR platforms. The invention replaces human sensor data analysts with hardware and software providing two significant advantages over the current manual methods.

In one or more embodiments of the invention, functional data analysts may use a functional data authoring module to capture functional metadata in a consistent manner. Conflict reports for the business processes may be generated for a subset of the business processes or as an overall report across all business processes. One or more embodiments of the invention may provide early detection of data usage and type conflicts from functional data requirements, automated detection of conflicts from functional data requirements, reports listing detected conflicts, conflicts resolution tracking mechanism, ongoing notification regarding changes in functional data requirements or detected conflicts, and avoidance of conflicting functional requirement in the realization phase, thereby reducing costs and project risks and avoiding project delays.

The invention discloses a method of constructing a big-data service model based on page dragging technology. The method realizes visualization setting of each node parameter in the service model through the page dragging technology, establishes relationships between nodes, forms the workflow model, and specifically includes the following steps: establishing a big-data platform user, namely an executor of the service model; configuring data sources; establishing the model, wherein the complete service model is constructed through dragging each service component; carrying out trial running of the model; releasing the model, wherein a model state is callable; carrying out model scheduling setting for periodically executing the service model; and running the model, wherein running operation of the model is executed according to time points of scheduling setting. According to the method, big-data services can be converted into visualization workflows of the component nodes for setting, development work of big-data developers can be simplified, and service personnel and data analysts can be enabled to participate in automation configuring of the workflows of the big-data services.

A system for analyzing data to determine an activity around a product is provided. The system comprises a user interface configured to enable one or more data analysts to provide input data and an acquisition module coupled to user interface and configured to retrieve social media data in response to the input data. The social media data is received from one or more social media platforms. The system further comprises a processing circuitry coupled to the acquisition module and comprises an analysis module configured to analyze the social media data to generate processed data and classify the processed data based on a plurality of criteria and a visualization module coupled to the analysis module and configured to generate a plurality of visual representations of classified data.

A night vision system includes an image intensifier tube and circuitry coupled to a digital storage medium that periodically samples a signal provided by the image intensifier tube and stores the sampled image to be viewed in near real time or at a later date by a data analyst. The night vision system includes a casing surrounding the image intensifier tube and the associated circuitry along with a port for accepting a power and / or signal cable for providing power to the image intensifier tube and image signal data to the digital storage medium. The system may further include a daytime camera and a switch for toggling the image signal data input to the digital storage medium between the daytime camera and the image intensifier tube.