Abstract: Disclosed are various embodiments for data anomaly detection. A variable profile is generated for each variable in source data. Then, the variable profiles are provided to each of a plurality of machine learning models. Next, it is determined, with each of the plurality of machine learning models, whether each variable profile is anomalous. The determination, from each of the plurality of machine learning models, whether each variable profile is anomalous is provided to an ensemble model. The ensemble model then generates a final determination whether each variable profile is anomalous. The final determination is then reported to an analysis service.

Abstract: The present application discloses a method, system, and computer system for running a test in a database system. The method includes obtaining, by one or more processors associated with a server, a template comprising one or more variables, storing, in a cache, a mapping of field definitions for a particular dataset, populating, by the one or more processors, the template to generate a populated template based at least in part on the mapping of field definitions for the particular dataset, performing, by the one or more processors, a query with respect to the particular dataset using values obtained from the populated template, and monitoring, by the one or more processors, one or more performance characteristics associated with the performing the query.

Abstract: A network health analyzer that analyzes health of a computer network may be implemented in accordance with an embodiment of the present invention. A network profile including an issue profile and one or more benchmarks appropriate for the network is determined. A set of numeric measures that is common to all issues in the issue profile is established. The network health analyzer collects data points pertaining to the operation of the network. Based on the data points, numeric values corresponding to the numeric measures may be calculated. In turn, health indexes for all issues in the issue profile may be determined. Based on these health indexes for the issues, an overall health rating may be determined.

Abstract: Techniques for quantitative converged network assessment are described. Performance information, associated with network infrastructure elements and application or service elements of a computer network, is received. One or more key performance indicators of a reference network architecture are compared with at least a portion of the performance information. A plurality of first scores is determined based on the comparison of the one or more key performance indicators and at least a portion of the performance information. Based on the plurality of first scores, a single second score is determined that indicates a converged state of the computer network with respect to the reference network architecture.

Abstract: A network health analyzer that analyzes health of a computer network may be implemented in accordance with an embodiment of the present invention. A network profile comprising an issue profile and one or more benchmarks appropriate for the network is determined. A set of numeric measures that is common to all issues in the issue profile is established. The network health analyzer collects data points pertaining to the operation of the network. Based on the data points, numeric values corresponding to the numeric measures may be calculated. In turn, health indexes for all issues in the issue profile may be determined. Based on these health indexes for the issues, an overall health rating may be determined.

Abstract: A network health analyzer that analyzes health of a computer network may be implemented in accordance with an embodiment of the present invention. A network profile comprising an issue profile and one or more benchmarks appropriate for the network is determined. A set of numeric measures that is common to all issues in the issue profile is established. The network health analyzer collects data points pertaining to the operation of the network. Based on the data points, numeric values corresponding to the numeric measures may be calculated. In turn, health indexes for all issues in the issue profile may be determined. Based on these health indexes for the issues, an overall health rating may be determined.

Abstract: Techniques for quantitative converged network assessment are described. Performance information, associated with network infrastructure elements and application or service elements of a computer network, is received. One or more key performance indicators of a reference network architecture are compared with at least a portion of the performance information. A plurality of first scores is determined based on the comparison of the one or more key performance indicators and at least a portion of the performance information. Based on the plurality of first scores, a single second score is determined that indicates a converged state of the computer network with respect to the reference network architecture.

Abstract: A network health analyzer that analyzes health of a computer network may be implemented in accordance with an embodiment of the present invention. A network profile comprising an issue profile and one or more benchmarks appropriate for the network is determined. A set of numeric measures that is common to all issues in the issue profile is established. The network health analyzer collects data points pertaining to the operation of the network. Based on the data points, numeric values corresponding to the numeric measures may be calculated. In turn, health indexes for all issues in the issue profile may be determined. Based on these health indexes for the issues, an overall health rating may be determined.

Abstract: A network health analyzer that analyzes health of a computer network may be implemented in accordance with an embodiment of the present invention. A network profile having an issue profile and one or more benchmarks appropriate for the network is determined. A set of numeric measures that is common to all issues in the issue profile is established. The network health analyzer collects data points pertaining to the operation of the network. Based on the data points, numeric values corresponding to the numeric measures may be calculated. In turn, health indexes for all issues in the issue profile may be determined. Based on these health indexes for the issues, an overall health rating may be determined.

Abstract: A network health analyzer that analyzes health of a computer network may be implemented in accordance with an embodiment of the present invention. A network profile comprising an issue profile and one or more benchmarks appropriate for the network is determined. A set of numeric measures that is common to all issues in the issue profile is established. The network health analyzer collects data points pertaining to the operation of the network. Based on the data points, numeric values corresponding to the numeric measures may be calculated. In turn, health indexes for all issues in the issue profile may be determined. Based on these health indexes for the issues, an overall health rating may be determined.

Abstract: Nano-scale DMC catalyst complexes are highly active alkylene oxide polymerization catalysts. Thy show a greatly improved ability to catalyze the formation of EO-capping onto secondary hydroxyl-terminated polyethers. The catalysts can be prepared by precipitation in the dispersed adequous phase of a water-in-oil emulsion.