Computer technology for transforming data in a data store (for example, a database) through a user interface (UI) in the form of a visualization diagram having human understandable visual information. A user interacts with the visualization diagram to effect desired transformations in the data of the data store.

Methods, systems, and apparatus for updating maintenance profiles of devices or equipment are disclosed herein. An updated device maintenance profile is generated based on an existing maintenance profile of a device via an operation that preserves the form logic of the former. An electronic change request is generated irrespective of the data structures in the maintenance profiles, and upon the approval of the request, the updated maintenance profile is activated as the operative maintenance profile of the device. Further, an audit trail recording the activities of the system updating the maintenance profiles of devices is generated.

According to one method, the method comprises: receiving, from a client via a REST API, input in a first format; converting, using predetermined metadata, the input in the first format into input in a second format; sending the input in the second format to a legacy system for performing an operation using the input in the second format; receiving, from the legacy system, output in the second format, wherein the output is based at least in part on the operation performed using the input in the second format; converting, using the predetermined metadata, the output in the second format into output in the first format; and sending, to the client via the REST API, the output in the first format.

Provided is a method for encoding scatterplot data using strings. The method may comprise receiving a plurality of data points in a data set. Each data point has at least a first data value corresponding to a first dimension and a second data value corresponding to a second dimension. The method further comprises determining a first resolution for the first dimension and a second resolution for the second dimension. The method further comprises determining an encoding scheme for encoding the plurality of data points. The encoding scheme includes a plurality of valid encoding characters. The method further comprises encoding each of the plurality of data points based on the first resolution, the second resolution, and the encoding scheme.

Methods, systems, and devices supporting querying disparate data sources are described. Querying disparate data sources may include receiving an input for data stored at a first data source from a plurality of data sources, selecting a first data connector from a plurality of data connectors, wherein the first data connector corresponds to the first data source, and identifying a first query language corresponding to the first data source from a plurality of query languages. Querying the disparate data sources may further include generating a converted query based at least in part on the first query language and retrieving the data from the first data source using the first data connector based at least in part on the converted query.

Systems and method for implementing deduplication process based on performance analyses. The system may include a processing device to determine a first performance metric associated with retrieving a second stored data block that is within a specified range of a duplicate of the first data block and a second performance metric associated with retrieving a hash value corresponding to the second stored data block. The processing device further to retrieve the second stored data block within a specified range of the duplicate of the first data block in response to the first performance metric not exceeding the second performance metric.

A data exchange that provides self-service data provisioning is provided. The data exchange may include a raw data layer, a model data layer, a plurality of workspaces and a testing environment. The raw data layer may be a landing zone for raw data records received from systems of record. The raw data layer may receive a plurality of raw data records, model and process the data records and transfer the data records to the model data layer. The model data layer may be a data layer that includes data modeled to data exchange specifications and enables queries to be executed on the data included in the model data layer. Each workspace may be allocated to a consumer. The consumer may query the plurality of data records within the model data layer. The testing environment may test scripts to ensure that the scripts conform to a predetermined set of testing specifications.

The present disclosure provides an integrated circuit chip device and a related product. The integrated circuit chip device includes: a primary processing circuit and a plurality of basic processing circuits. The primary processing circuit or at least one of the plurality of basic processing circuits includes the compression mapping circuits configured to perform compression on each data of a neural network operation. The technical solution provided by the present disclosure has the advantages of a small amount of computations and low power consumption.

The disclosed systems and methods may receive a data record from either a legacy data source or a modern data source and determine whether the record satisfies a first set of validation rules. When the record fails to satisfy the first set of rules, reject the record for storage in a data store. When the record satisfies the first set of rules, determine whether the record satisfies a second set of validation rules. When the record satisfies the second set of rules, store the record in the data store with an indicator that the record satisfies the all rules. When the record fails to satisfy the second set of rules, if the source was a modern data source reject the record, and if the source was a legacy data source store the record in the data store with an indicator that it fails to satisfy the second set of rules.

A system for extracting latent information from data includes obtaining or generating components of the data, where the data components include scores indicating how the component relates to the data. Memory is allocated for the components and the components are stored in the allocated memory. The components are then transformed into documents using a suitable transformation function, and the documents are analyzed using natural language processing, to extract latent information contained in the data.