System and method for analyzing and reporting extensible data from multiple sources in multiple formats

• US 20070022093A1
• Filed: 03/07/2006
• Published: 01/25/2007
• Est. Priority Date: 03/07/2005
• Status: Active Grant

• Current Assignee: Citrix Systems, Inc. (Cloud Software Group)
• Original Assignee: Skytide (Cloud Software Group)
• Inventors: Wyatt, Nat, Rozenfeld, Joseph
• Granted Patent: US 7,630,956 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing

Abstract

A system and method for analyzing and reporting data from multiple sources is provided. The system is a foundation for an analytical platform that covers not only traditional relational data, but also a new generation of extensible data formats designed for the web, such as those based on XML (FIXML, FpML, ebXML, XBRL, ACORD, etc.), as well as HTML, E-mail, Excel, PDF, and others. In a preferred embodiment, the eXtensible on-line analytical processing (XOLAP), is a scalable client/server platform that allows the multi-dimensional analysis of modern data types, as well as traditional relational data, by bringing them all into an internal common XML-based model, without the time and expense of creating a data warehouse.

Claims

1. An extended online analytical server, comprising:

one or more adaptors, each adaptor converting one or more pieces of data from a particular data source having a particular data format into the common data format;

an aggregator that aggregates the one or more pieces of data from the data sources to generate aggregated pieces of data;

a virtual schema generator that generates a virtual schema from the aggregated pieces of data;

an indexing engine and a scheduler that update the virtual schema when new pieces of data are received by the aggregator;

an analytical cube generator that generates an analytical cube based on the virtual schema; and

an application programming interface to an external tool wherein the application programming interface permits the external tool to access the piece of data in the analytical cube.

2. The server of claim 1 further comprising one or more report definitions stored in the server, each report definition defining a report to be generated based on the pieces of data in the analytical cube.

3. The server of claim 1 further comprising a cache that stores the virtual schema.

4. A computer-implemented method for analyzing and reporting data from multiple data sources, the method comprising:

storing one or more pieces of data from one or more data sources wherein the data sources include at least relational data sources and non-relational data sources;

converting one or more pieces of data from the data sources into a common data format;

generating an analytical cube based on the one or more pieces of data in the common data format using a declarative language; and

providing an application programming interface to an external tool wherein the application programming interface permits the external tool to access the piece of data in the analytic cube.

5. The method of claim 4, wherein the external tool further comprises one or more of a business intelligence tool, a reporting application and an analytic tool.

6. The method of claim 4 further comprising receiving the one or more pieces of data from each data sources using an adaptor wherein the adaptor converts the one or more pieces of data from a particular data source having a particular format into the common data format.

7. The method of claim 4, wherein the common data format further comprises XML.

8. The method of claim 7, wherein the one or more data sources further comprises on or more of an XML data source, an HTML data source, an email data source, an excel data source, a PDF data source and a flat file data source.

9. The method of claim 4, wherein the declarative language further comprises xPath.

10. An apparatus for analyzing and reporting data from multiple data sources, the apparatus comprising:

an adaptor that allows a data source with one or more data items having a particular data format to be loaded into an extended online analytical processing system that converts the data items from the different data sources into a common format and generates a multidimensional analytical cube based on the data items; and

an application programming interface to an external tool wherein the application programming interface permits the external tool to access the piece of data in the analytical cube.

11. A computer-implemented method for generating dimensional analytical models from extensible data, the method comprising:

receiving one or more pieces of data from one or more data sources wherein the data sources include at least one of a relational data source and a non-relational data sources;

converting the one or more pieces of data from the one or more data sources into a common data format;

forming a dimensional analytical model for the one or more pieces of data stored in the common format; and

wherein forming the dimensional analytical model further comprises using a declarative language to describe the dimensional analytical model.

12. The method of claim 11, wherein the declarative language further comprises xPath.

13. The method of claim 11 further comprising performing path analysis using the dimensional analytical model wherein the path analysis is based on the declaration language.

14. The method of claim 13, wherein performing path analysis further uncovering data about a sequence of events contained in the one or more pieces of data.

15. The method of claim 11 further comprising identifying, using the dimensional analytical model, co-occurrences between the one or more pieces of data.

16. The method of claim 11 further comprising determining an aggregated value for a particular piece of data from the one or more pieces of data wherein a first set of pieces of data has a first hierarchical structure that contains the particular piece of data and a second set of pieces of data has a second hierarchical structure that contains the particular piece of data at a different location than the first hierarchical structure, and wherein determining the aggregated value further comprises extracting the particular piece of data from each hierarchical structure using the dimensional analytical model.