Oracle International Corporation

Saugata Chowdhury

Alextair Dominico Mascarenhas

Raghuram Venkatasubramanian

Roger Bolsius

Victor Belyaev

Ashish Mittal

Samar Lotia

Alvin Raj

Gabby Rubin

John Fuller

Ananth Venkata

Jacques Vigeant

Harvard Pan

Venugopal Surendran

Ling Ni

Donko Donjerkovic

Steve Simon Joseph Fernandez

Ispati Nautiyal

Jagdish Chand

Vijayakumar Ranganathan

Akshay Satyendranath

Dmitriy Gertsman

Saurav Mohapatra

Krishnan R Subramaniam

Systems and methods for providing a universal format driven data transformation. In conventional ETL operations, the transform process that transforms data from the source format to the destination format is based on a transformation program. Conventionally, transform logic is developed around the chosen transform program. In accordance with an embodiment, a universal, format-driven data transform can be achieved through the use of a data transformation format. In accordance with an embodiment, a method for providing a universal format driven data transformation can include providing a transformation format in a file, wherein the transformation format is in a human-readable form; and providing, in the transformation format, keywords defining a target table type, a dataset list, and dataset operations to be performed on a dataset from the dataset list.

System and method for universal format driven data transformation and key flex fields in an analytic applications environment

In accordance with an embodiment, described herein is a system and method for loading and transforming data to a cloud database, using a hybrid set-based extract, load, transform approach. During the loading and transforming of large amounts of data, from one or more data sources, a data synchronization application sends small batches of data, in parallel streams, to the database, which operates as a transformation engine to load the data. Each stream can be associated with a separate staging table in the database. For each staging table, the subset of data therein is transformed and loaded, before the next subset is processed. A transform and merge process operating at the database can then be used to transform and merge the data, from each of the staging tables, to the target table.

System and method for providing a hybrid set-based extract, load, and transformation of data

In accordance with various embodiments, described herein are systems and methods for use of computer-implemented machine learning to automatically determine insights of facts, segments, outliers, or other information associated with a set of data, for use in generating visualizations of the data. In accordance with an embodiment, the system can receive a data set that includes data points having data values and attributes, and a target attribute, and use a machine learning process to automatically determine one or more other attributes as driving factors for the target attribute, based on, for example, the use of a decision tree and a comparison of information gain, Gini, or other indices associated with attributes in the data set. Information describing facts associated with the data set can be graphically displayed at a user interface, as visualizations, and used as a starting point for further analysis of the data set.

System and method for data visualization using machine learning and automatic insight of facts associated with a set of data

In accordance with various embodiments, described herein are systems and methods for use of computer-implemented machine learning to automatically determine insights of facts, segments, outliers, or other information associated with a set of data, for use in generating visualizations of the data. In accordance with an embodiment, the system can use a machine learning process to automatically determine one or more outliers or findings within the data, based on, for example, determining a plurality of combinations representing pairs of attribute dimensions within a data set, from which a general explanation or pattern can be determined for one or more attributes, and then comparing particular values for attributes, with the determined pattern for those attributes. Information describing such outliers or findings can be graphically displayed at a user interface, as text, graphs, charts, or other types of visualizations, and used as a starting point for further analysis of the data set.

System and method for data visualization using machine learning and automatic insight of outliers associated with a set of data

System and method for universal format driven data transformation and key flex fields in a analytic applications environment

A business intelligence (BI) server is described that supports data and schemas stored in multiple languages. The BI server implements a lookup table and lookup function that allows users to work with queries in different languages. When the user logs in, a session object is created for the user, which maintains the state information. A session variable specifies the language currently being used by the user. The BI server can inspect this session variable to determine the language of the user and perform the lookup translations as necessary. For example, if the language used by the session is different from the language of the base table storing the necessary information, the BI server can perform a translation by invoking a lookup function. The execution of the lookup can include performing a join operation of the base table with the lookup table to yield a translated value requested by the query.

Systems and methods for providing multilingual support for data used with a business intelligence server

An administration tool can be used to provide data flexibility in a business intelligence (BI) server that is associated with a data warehouse. The administration tool can display one or more data objects that are adapted to be imported from an application framework into a physical model maintained on the BI server. The administration tool can further map the one or more data objects in the physical model into a logical model, also maintained on the BI server, which corresponds to at least one target table in the data warehouse. Additionally, the administration tool can publish an extension input to an extender associated with the data warehouse based on the logical model, wherein the extender operates to generate one or more metadata extensions based on the extension input.

System and method for providing data flexibility in a business intelligence server using an administration tool

An input extension specification can be generated, via an administration tool on a business intelligence (BI) server, for an extender associated with a data warehouse in order to extend the data warehouse. The administration tool can request for data flow information of the data warehouse from the extender. The data flow information indicates the mapping relationship between one or more source data objects and one or more target tables in the data warehouse. The administration tool further allows a user to select said one or more target tables in the data warehouse to be extended based on the data flow information, and builds the input extension specification for the extender.

System and method for specifying metadata extension input for extending data warehouse

A business intelligence (BI) server and repository are described which support a set of customized and/or calculated data members. In accordance with an embodiment, the BI server maintains a connection to a plurality of data sources which may store a set of dimension members. The data source can be relational, file storage based, multidimensional and other types. In accordance with an embodiment, the BI server can accept queries from the user that contain calculated members as a parameter. The calculated member is defined by an expression including multiple dimension members and one or more arithmetic operators. The BI server can parse and validate the query and rewrite the query for the data source. After the query is rewritten and optimized, it is executed against the data source and a set of results is received.

Systems and methods for providing custom or calculated data members in queries of a business intelligence server

An extender associated with a data warehouse can support metadata extension for the data warehouse. The extender can create an ETL extension plan for extending the data warehouse. The ETL extension plan includes one or more ETL plan elements that indicate extensions on ETL metadata objects. The one or more ETL plan elements within the ETL extension plan can be ordered, and ETL metadata extension can be performed based on the ETL extension plan.

System and method for supporting data warehouse metadata extension using an extender

A business intelligence (BI) server and repository are described which support a set of hierarchical relationships among the data. The BI server receives user input specifying a set of parent-child or other ancestral relationship among a set of data in a data source. The BI server generates a set of SQL queries and executes the queries to pre-populate a set of tables which specify the parent child relationships among the data in the data source. One such table is a parent-child relationship closure table that defines the inter-member relationships among the data members. Once the tables are populated, the BI server uses the closure tables to answer queries that require knowledge of the ancestral relationships among data.

Systems and methods for providing value hierarchies, ragged hierarchies and skip-level hierarchies in a business intelligence server

A solution is provided in which regions are formed incrementally as points are added to a database. Each time a point is added to the database, it may be assigned to a new region. This new region may then be compared against each of the current set of regions until one is found with which it can be successfully merged. Then, this newly merged region may be compared against each of the other regions until one is found with which it can be successfully merged. This process repeats until there are no more regions that can be merged. Determining whether or not a region can be merged with another region may involve determining whether or not the points in one region differ from the points in the other region only along one dimension. If so, then the point can be successfully merged with the region.

Growing community of inventors

Sunnyvale, CA, United States of America

Saugata Chowdhury