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.

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.

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.

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.

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 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.

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.