International Business Machines Corporation

Robert J McKeown

Randy George

Alexander Pikovsky

David Joel Pennell, Sr

Ryan A Garrett

Colin Putney

Patrick Joseph O'Sullivan

Anthony T Brew

Michael D Uftring

Data stream quality management for analytic environments includes deploying, into a runtime environment upstream from an analytic module, an ingress quality specification (IQS) module. The IQS module receives a data stream and analyzes a subset of data of the data stream to determine if the subset of data meets a quality expectation of the analytic module. The subset of data is annotated to indicate a quality status based on whether the subset of data meets the quality expectation of the analytic module. The data stream is output with the annotated subset of data to the analytic module, and the analytic module analyzes the data stream to assess an operating characteristic of an upstream device.

Data stream quality management for analytic environments

Data stream quality management for analytic environments includes an ingress quality specification (IQS) module with a data stream analytic module. The analytic module has a data quality expectation for data of the data stream and receives the data stream from the IQS module. A selector module receives the data stream from an object and selects a subset of the received data stream. A predicate module applies a predicate to the subset to determine if the subset meets the quality expectation of the analytic module. The predicate module modifies the subset of data by annotating the subset to indicate a quality status based on whether the subset meets the quality expectation. The IQS module outputs the data stream with the annotated subset of data to the analytic module. The analytic module outputs an analysis of the object based on whether the annotated subset of data met the quality expectation.

A computer program product for selecting time-series data is provided. The computer program product includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and executable by a processing circuit to cause the processing circuit to assemble, by the processing circuit, a set of analytic assessment tools for time-series data, engage, by the processing circuit, the analytic assessment tools to measure characteristics-of-importance in a relevant analytic domain for sets of the time-series data, generate, by the processing circuit, as a measurement result, a score for each set of the time-series data based on the associated characteristics-of-importance and rank, by the processing circuit, the sets of the time-series data in accordance with the score for each set of the time-series data for subsequent time-series data selection.

Selecting time-series data for information technology (IT) operations analytics anomaly detection

A computer program product is provided and includes a storage medium having program instructions. The program instructions are readable and executable by a processing circuit to cause the processing circuit to determine from historical data which anomaly detectors are associated with key performance indicators (KPIs), to extract descriptors of the first metric group from the KPIs to create a first feature profile thereof, to repeat the determining and the extracting with respect to historical data of second and third metric groups to create second and third feature profiles thereof, respectively, to ascertain which of the second and third feature profiles has a greater correlation to the first feature profile and to rank the second and third feature profiles based on which one has the greater correlation and compare the higher ranked one to future metrics in current or subsequent environments to determine if specific KPIs are likely to produce anomalies.

Selecting key performance indicators for anomaly detection analytics

According to one aspect of the present disclosure, a method and technique for data quality management is disclosed. The method includes: deploying, into a runtime environment with a data stream analytic module, an ingress quality specification (IQS) module associated with the analytic module; receiving, by the IQS module, the data stream; analyzing, by the IQS module, a subset of data of the data stream to determine if the subset of data meets a quality expectation of the analytic module; annotating the subset of data to indicate a quality status based on whether the subset of data meets the quality expectation of the analytic module; and outputting the data stream to the analytic module.

According to one aspect of the present disclosure, a system and technique for data quality management is disclosed. The system includes a processor and an ingress quality specification (IQS) module executable by the processor in a runtime environment with a data stream analytic module. The IQS module is configured to: receive the data stream; analyze a subset of data of the data stream to determine if the subset of data meets a quality expectation of the analytic module; annotate the subset of data to indicate a quality status based on whether the subset of data meets the quality expectation of the analytic module; and output the data stream to the analytic module.

A method and system for managing software application states selects a plurality of stateful applications for reinstatement at a later time. A set of data contexts is generated based on the selected applications. The set of data contexts is pushed onto a data stack. Thereafter the set of data contexts is popped from the data stack for reinstatement. Each step or function may be initiated automatically or through user input, and may be used in a single-user, multi-user or collaborative setting.

Managing multi-application contexts

An embodiment of the invention comprises, providing an initial object graph to a database, the initial object graph being generated by applying a set of rules to resources included in a resource set at a specified time, or by revising a previous object graph at the previous time, the resource set at the specified time comprising an initial resource set. The method includes providing the initial object graph to a working memory, maintained in separation from the database; discovering a changed fact associated with one of the resources of the initial resource set; and upon discovering the changed fact, determining modifications required by the changed fact to the initial object graph. If modifications are required, the initial object graph is revised in the working memory to include such modifications. The same revisions are then made to the initial object graph in the system database.

Creation and revision of network object graph topology for a network performance management system

A method, system, and computer usable program product for deploying analytic functions are provided in the illustrative embodiments. A resource is identified in an analytic function specification. A set of input time series is identified for the analytic function specification. An analytic function instance corresponding to the analytic function specification is instantiated in relation to an object of the resource. Each input time series in the set of time series is located in relation to the object. The analytic function instance is associated with each input time series in the set of time series. An analysis is performed using the set of input time series and an analytic function described in the analytic function specification. The analytic function instance is instantiated if both the object and the set of data sources are present in an object graph where the analytic function instance is to be instantiated.

Growing community of inventors

Newburyport, MA, United States of America

Robert J McKeown