Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: Techniques for discovering semantic meaning of data in fields included in one or more data sets, the method including: a first field having a previously-assigned label that indicates a semantic meaning of the first field; identifying a set of one or more candidate labels, for potential assignment to the first field instead of the previously-assigned label; evaluating, using a previously-determined label score and a first candidate label score, whether to assign a first candidate label to the first field, the evaluating comprising: when the first candidate label score is at least a first threshold amount greater than a previously-determined label score, presenting the first candidate label to a user by generating an interface through which the user can provide input indicating whether to assign the first candidate label to the first field instead of the previously-determined label.

Abstract: Techniques for an Application Programming Interface (API) gateway to workload placement and load balancing in a distributed system. The API gateway may route API requests, responses, and so forth, via a plurality of paths between the API gateway, API endpoint devices and API client devices. The API gateway may collect the path properties for the plurality of paths between itself, and the client devices and API endpoints. Additionally, or alternatively, the API gateway may collect process properties indicating the statistics of specific processes. Using this data, the API gateway may determine that a particular path, a particular process, etc., has experienced performance degradation. The API gateway may further determine, and perform, a remedial action to take to remedy the performance degradation of the path or processes.

Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: Techniques for discovering semantic meaning of data in fields included in one or more data sets, the method including: a first field having a previously-assigned label that indicates a semantic meaning of the first field; identifying a set of one or more candidate labels, for potential assignment to the first field instead of the previously-assigned label; evaluating, using a previously-determined label score and a first candidate label score, whether to assign a first candidate label to the first field, the evaluating comprising: when the first candidate label score is at least a first threshold amount greater than a previously-determined label score, presenting the first candidate label to a user by generating an interface through which the user can provide input indicating whether to assign the first candidate label to the first field instead of the previously-determined label.

Abstract: Techniques for using application network requirements and/or telemetry information from a first networking technology to enhance operation of a second networking technology and optimize wide area network traffic are described herein. The techniques may include establishing a communication network for use by applications of a scalable application service platform, the communication network including a first networking technology and a second networking technology. In this way, a request to establish a connection for use by an application may be received by the first networking technology. The request may include an indication of a threshold service level of the connection. In response to the request, the first networking technology may determine whether the second networking technology is capable of hosting the connection.

Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: Techniques for an Application Programming Interface (API) gateway to workload placement and load balancing in a distributed system. The API gateway may route API requests, responses, and so forth, via a plurality of paths between the API gateway, API endpoint devices and API client devices. The API gateway may collect the path properties for the plurality of paths between itself, and the client devices and API endpoints. Additionally, or alternatively, the API gateway may collect process properties indicating the statistics of specific processes. Using this data, the API gateway may determine that a particular path, a particular process, etc., has experienced performance degradation. The API gateway may further determine, and perform, a remedial action to take to remedy the performance degradation of the path or processes.

Abstract: A method for updating a computer program includes receiving a computer program hosted on and configured to be executed by a first computing system. The method includes analyzing the computer program to obtain characterization of a lineage, an architecture, and an operation of the computer program. The lineage includes relationships among elements of the computer program, the architecture includes a characteristic of the data source, the data target, and one or more processors configured to process the data contained in data records, and the operation includes processes that are executed to process the data from the data records.

Abstract: Techniques for using application network requirements and/or telemetry information from a first networking technology to enhance operation of a second networking technology and optimize wide area network traffic are described herein. The techniques may include establishing a communication network for use by applications of a scalable application service platform, the communication network including a first networking technology and a second networking technology. In this way, a request to establish a connection for use by an application may be received by the first networking technology. The request may include an indication of a threshold service level of the connection. In response to the request, the first networking technology may determine whether the second networking technology is capable of hosting the connection.

Abstract: A method for analyzing a computer program ecosystem includes performing a static analysis, including identifying static dependencies among elements of the ecosystem based on values of parameters in one or more parameter sets associated with the ecosystem, the elements of the ecosystem including the computer programs of the ecosystem and data resources associated with the computer programs. The method includes performing a runtime analysis, including identifying elements of the ecosystem that were utilized during execution of the ecosystem to process data records. The method includes performing a schedule analysis, including identifying a computer program of the ecosystem that has a schedule dependency from another computer program of the ecosystem. The method includes identifying a subset of the elements of the ecosystem as an ecosystem unit based on the results of the static, runtime, and schedule analyses. The method includes migrating the ecosystem unit, testing the ecosystem unit, or both.

Abstract: An audio device includes a casing configured for operation in a first orientation and a second orientation different from the first orientation, an orientation input device disposed on the casing to detect an orientation of the casing relative to the direction of the force of gravity, and a plurality of acoustic drivers disposed on the casing and operable to form a plurality of acoustic interference arrays, each of which is associated with one of a plurality of audio channels. The acoustic drivers of the audio device operate in a first frequency range and modify at least one of the acoustic interference arrays in response to a change in the orientation detected by the orientation input device.