International Business Machines Corporation

Protegrity Corporation

Hitachi Vantara Corporation

Exeros, Inc.

Lingling Yan

Alexander Gorelik

Yigal Rozenberg

Vichai Levy

Mauricio Antonio Hernandez-Sherrington

David Clyde Williamson

Hans Meijer

Mary Ann Roth

Lucian Popa

Ching-Tien Ho

Ronald Fagin

Laura Myers Haas

Daina Edvina Pupons Wickham

Renee J Miller

Leon Burda

Robert LaVerne Hobbs

Felix Gerhard Naumann

Shayak Sadhu

Kiranmayi Potu

In some examples, a system receives a user input to create a classification to use for a first data set. In addition, the system may receive a user input to associate the classification with the first data set as reference data. The system may determine a classification association with the first data set based in part on comparing a first classification model corresponding to the reference data with a second classification model of a second data set, the second classification model being determined based at least in part on a plurality of data properties of the second data set. Further, the system may determine a user curation result with respect to the classification association with the first data set, and may update the classification model for the first data set based at least in part on the user curation result.

Data cataloging based on classification models

A gateway device includes a network interface connected to data sources, and computer instructions, that when executed cause a processor to access data portions from the data sources. The processor accesses classification rules, which are configured to classify a data portion of the plurality of data portions as sensitive data in response to the data portion satisfying the rule. Each rule is associated with a significance factor representative of an accuracy of the classification rule. The processor applies each of the set of classification rules to a data portion to obtain an output of whether the data is sensitive data. The output are weighed by significance factors to produce a set of weighted outputs. The processor determines if the data portion is sensitive data by aggregating the set of weighted outputs, and presents the determination in a user interface. Security operations may also be performed on the data portion.

Sensitive data classification

Various embodiments of a method, system and article of manufacture to discover relationships among a first set of elements and a second set of elements are provided. At least one metric algorithm is identified based on a metric selection parameter. A raw result is determined based on the at least one metric algorithm, a first specified structural description of the first set of elements and a second specified structural description of the second set of elements. The raw result comprises a plurality of relationship measurements and the raw result is ordered. In some embodiments, a balanced result is produced based on the raw result and a matching strategy algorithm. In other embodiments, the matching strategy algorithm is identified based on a matching strategy selection parameter.

Tolerant and extensible discovery of relationships in data using structural information and data analysis

An apparatus and method are described for the discovery of semantics, relationships and mappings between data in different software applications, databases, files, reports, messages, or systems. In one aspect, semantics and relationships and mappings are identified between a first and a second data source. A binding condition is discovered between portions of data in the first and the second data source. The binding condition is used to discover correlations between portions of data in the first and the second data source. The binding condition and the correlations are used to discover a transformation function between portions of data in the first and the second data source.

Semantic discovery and mapping between data sources

In one aspect, semantics and relationships and mappings are identified between a first and a second data source. Data between the first and second data source is compared. A binding condition is discovered between portions of data in the first and the second data source based upon the comparison, wherein the binding condition identifies data within the first and second data sources that map to each other. The binding condition is used to discover correlations between portions of data in the first and the second data source, wherein the correlations identify data in the first data source that correspond to values in the second data source. The binding condition and the correlations are used to discover a transformation function between portions of data in the first and the second data source, wherein the transformation function generates data in the second data source data in the first data source.

Techniques are provided for viewing mappings between objects. A main view is displayed, wherein the main view shows one or more source objects, one or more target objects, and zero or more mappings between the one or more source objects and the one or more target objects. Input selecting a type of view to be displayed in the main view is received, wherein each type of view provides a different amount of detail regarding the mappings. In response to receiving the input, the selected type of view is created, and the created view is displayed. Additionally, techniques are provided for viewing objects. One or more objects along with mappings between the one or more objects are displayed. View filters are provided that may be applied to the one or more objects, wherein the view filters enable hiding at least one of mapped or unmapped objects. Moreover, techniques are provided for viewing nodes. A structure is displayed that includes one or more nodes. A hide option is provided that may be applied to the one or more displayed nodes, wherein selection of the hide option hides one or more selected nodes of the displayed nodes and descendants of the selected nodes.

Techniques for viewing mappings and nodes

Method and apparatus for semantic discovery and mapping between data sources

A computer program product is provided that uses data examples as a basis for understanding and refining declarative schema mappings. The system of the present invention identifies a set of intuitive operators for manipulating examples including establishing value correspondences, data linking, data trimming, data walking, and data chasing. These operators allow a user to follow and refine an example by walking through a data source. In addition, these operators can identify a large class of schema mappings and distinguish effectively between alternative schema mappings. With these operators, a user is able to quickly and intuitively build and refine complex data transformation queries that map one data source into another while continuously verifying that the mapping is accurate and appropriate.

Method for schema mapping and data transformation

Growing community of inventors

Morgan Hill, CA, United States of America

Lingling Yan