Oracle International Corporation

Rahul V Herwadkar

Eric Hsiao

Jeffrey Toillion

Xiaochao Zhou

James Dang

Leon Zeng

Joydip Kundu

Anindya Chandra Patthak

A data analysis system is provided that enables users to perform complex data analyses based upon data that may be spread across multiple data sources. The data analysis system is configured to generate a combined query that is capable of extracting data from the multiple data sources. The user may provide analysis information describing the analysis the user desires to perform on the extracted data. In response, the data analysis system is further configured to automatically augment the combined query with program or code to implement the user-specified analysis. Execution of the augmented or modified combined query generates an analysis result set resulting from performing the user-specified analysis. The data analysis system provides a flexible and easy-to-use platform for a user, even a non-technical user, to perform complex data analyses using data stored in multiple different data sources.

Automated data analysis using combined queries

Techniques for detecting an anomaly in queries of a relational database are disclosed. The techniques include identifying a set of attribute values from a query for accessing data within a database. Based on previously received queries, at least one of a joint probability for the set of attribute values or individual probabilities for the set of attribute values is determined. When at least one of the joint probability for the set of attribute values or an individual probability for one or more attribute values in the set of attribute values does not satisfy a probability cutoff, an indication that the query is anomalous is outputted.

Distribution-based analysis of queries for anomaly detection with adaptive thresholding

Techniques for managing risks with continuous queries are provided. In some examples, a selection of a data object enabled to provide a real-time stream of business event data may be received. The selection may be received by a user associated with the business event data. Additionally, a continuous query language query may be generated. The query may be configured to monitor the real-time stream of business event data for a first metric. In some examples, the a risk indicator associated with a second metric that affects the first metric may be identified. Output events of a pre-existing continuous query language query may be listened to. Further, a real-time visualization of the first metric and/or the second metric may be provided.

Managing risk with continuous queries

The invention provides novel systems, methods and software for business activity monitoring. In one aspect of the invention, for example, events can be monitored and/or evaluated before the data is stored in a database. This can provide for real-time business activity monitoring and, in some cases, can prevent the database from becoming a bottleneck in the monitoring process. Merely by way of example, a business activity monitor process might be implemented in a middleware layer between an enterprise application and the database that is used to store data for the application.

Growing community of inventors

Foster City, CA, United States of America

Rahul V Herwadkar