CROSS-CATEGORY VIEW OF A DATASET USING AN ANALYTIC PLATFORM

• US 20090018996A1
• Filed: 01/28/2008
• Published: 01/15/2009
• Est. Priority Date: 01/26/2007
• Status: Active Grant

• Current Assignee: Information Resources Incorporated
• Original Assignee: Information Resources Incorporated
• Inventors: Hunt, Herbert Dennis, Agostinelli, Alberto, Johnson, Arvid C., Bergeon, Cheryl G., Hudson, Gregory David Neil, Basilico, Andrea, Gibbs, Marshall Ashby, Chapa, Craig Joseph, Yusko, Jay Alan, Griglione, Bradley Michael, Mason, Trevor, West, John Randall
• Granted Patent: US 10,621,203 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2264 Multidimensional index structures
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

In embodiments, systems and methods may involve using a platform as disclosed herein for applications described herein where the systems and methods involve receiving a dataset in an analytic platform, the dataset including fact data and dimension data for a plurality of distinct product categories. It may also involve storing the data in a flexible hierarchy, the hierarchy allowing the temporary fixing of data along a dimension and flexible querying along other dimensions of the data. It may also involve pre-aggregating certain combinations of data to facilitate rapid querying, the pre-aggregation based on the nature of common queries. It may also involve facilitating the presentation of a cross-category view of an analytic query of the dataset. In embodiments, the temporarily fixed dimension can be rendered flexible upon an action by the user.

Claims

1. A method comprising:

receiving a dataset in an analytic platform, the dataset including fact data and dimension data for a plurality of distinct product categories;

storing the data in a flexible hierarchy, the hierarchy allowing the temporary fixing of data along a dimension and flexible querying along other dimensions of the data;

pre-aggregating certain combinations of data to facilitate rapid querying, the pre-aggregation based on the nature of common queries; and

facilitating the presentation of a cross-category view of an analytic query of the dataset.