Teradata US, Inc.

Jason Keith Figge

Michael Chaves

Harold R Lee

Scott Shelton

Henry Fu

David Brophy

David Carmer

Anish Shah

Dennis Tackett

Rajeswara Rao Kottu

Leslie Mannion

Robert Baril

Corey Antwan Parham

Sreenath Madasu

Claud Teeter

Christian Seifert

Dan Willoughby

Sean Pritchard

Jeffrey Canna

Alex Chapman

Anil Peres-da-Silva

Steven Kennedy

A vendor is authenticated for use of a retailer's data warehouse and limited access rights are assigned to the vendor for access. The vendor accesses a graphical user interface (GUI) to select an available analysis module for execution against the data warehouse. Schemas are presented in the GUI based on the access rights, and specific schema selections are made by the vendor. The analysis module is then configured and executed against the data warehouse and filtered results are presented to the vendor; the results filtered based on the access rights assigned to the vendor.

Securely extending analytics within a data warehouse environment

The subject mater herein relates to requesting data from a database and, more particularly, to database query table substitution. Various embodiments provide systems, methods, and software to evaluate requests for data from a database and make table substitutions in the request to reduce a number of tables queried. Some embodiments include receiving a data request including data from two or more database table columns and building a list of all database tables specified in the data request. Some such embodiments further include, for each column in the data request, identifying each table from the list of all tables within which the column is present and identifying a least number of one or more tables that together include all of the columns of the data request. The data request may then be modified by changing the table of one or more of the columns in the received data requests.

Database query table substitution

Techniques are presented for tracking status within object chains. Global objects are associated with unique identifiers and each dependent local object created within the context of a particular global object receives that particular global object's identifier. A unique counter value is maintained for each status type of each global object. The local object facilitates communicating changes in its status using the received global identifier, and the counter values are updated accordingly for the affected global object.

Techniques for tracking status within object chains

Tools for defining and using custom analysis modules are presented. A generic graphical user interface (GUI) custom analysis tool is presented to a user. The generic GUI custom analysis tool is adapted to receive selections and inputs from the user that define many-to-many relationships in a data store and that include user-defined measures. The inputs are used to generate an instance of a custom analysis module that is capable of being processed against the data store. The instance of the custom analysis module may be stored, recalled, executed, and/or modified from the generic GUI custom analysis tool.

Tools for defining and using custom analysis modules

Techniques are presented for generic data extraction. Metadata defines a data extraction element with reference to an identifier, a data source, and one or more rules. The metadata may be processed to populate the data extraction element when a reference is made within a data template to the identifier. The identifier may be used to import data to a template or to export data to a different template or service.

Techniques for generic data extraction

Techniques are presented for synchronizing data store tables. Elements of first tables are linked together to form dependent chains. The dependencies are not housed with the elements in the first tables; rather, the dependencies are housed in multiple second tables. Each second table maps one of the elements from one of the first tables to another of the elements in another of the first tables.

Techniques for synchronizing data store tables

Techniques are presented for reusing business measures within a data store. A measure is associated with a measure type. Each measure is associated with a particular data store schema or schema element and includes metadata for fields and calculations against those fields. Requestors can select existing measures, create new measures, delete existing measures, and/or modify existing measures. A measure, when processed against the data store, produces results from a data store that are associated with the data store schema or the schema element and which conform to the fields and calculations defined within the measure's metadata.

Reusable measures

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Pittsboro, NC, United States of America

Jason Keith Figge