Systems and methods of mapping multidimensional data and executing queries

• US 8,990,212 B1
• Filed: 03/27/2014
• Issued: 03/24/2015
• Est. Priority Date: 03/27/2014
• Status: Active Grant

• Current Assignee: Visier Solutions Inc. (Visier, Inc.)
• Original Assignee: Visier Solutions Inc. (Visier, Inc.)
• Inventors: Zenger, Geoffrey Benjamin
• Primary Examiner(s): Corrielus, Jean M
• Application Number:
  US14/227,658
• Time in Patent Office: 362 Days
• Field of Search: 707/737
• US Class Current: 707/737
• CPC Class Codes: G06F 16/2282 Tablespace storage structures; Management thereof
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP

Abstract

A method includes identifying a source fact table, where the source fact table includes a first set of dimensions and corresponds to a source multidimensional cube that is associated with a first set of measures. The method also includes identifying a mapped multidimensional cube, where the mapped multidimensional cube is associated with a second set of dimensions and a second set of measures. The method further includes adding, to the source fact table, a one or more mapped dimensions corresponding to the second set of dimensions. The method includes associating, with the source multidimensional cube, one or more mapped measures corresponding to the second set of measures.

Claims

1. An analytics engine comprising:

a processor; and

a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising;

identifying a source fact table, wherein the source fact table includes a first set of dimensions and corresponds to a source multidimensional cube that is associated with a first set of measures;

identifying a mapped multidimensional cube, wherein the mapped multidimensional cube is associated with a second set of dimensions and a second set of measures;

adding, to the source fact table, one or more mapped dimensions corresponding to the second set of dimensions; and

associating, with the source multidimensional cube, one or more mapped measures corresponding to the second set of measures.

2. The analytics engine of claim 1, wherein the operations further comprise adding a calculated value to the source fact table, wherein the calculated value corresponds to a formula that is evaluated during query execution based on execution of a particular measure of the second set of measures.

3. The analytics engine of claim 1, wherein the source fact table includes a mapping key dimension and wherein the mapped multidimensional cube is associated with a dimension that corresponds to the mapping key dimension.

4. The analytics engine of claim 3, wherein a value of the mapping key dimension for a particular fact uniquely identifies the particular fact of the source fact table.

5. The analytics engine of claim 1, wherein the operations further comprise:

identifying a second mapped multidimensional cube, wherein the second mapped multidimensional cube is associated with a third set of dimensions and a third set of measures;

adding, to the source fact table, one or more additional mapped dimensions corresponding to the third set of dimensions; and

associating, with the source multidimensional cube, one or more additional mapped measures corresponding to the third set of measures.

6. The analytics engine of claim 1, wherein the source fact table comprises an employees fact table.

7. The analytics engine of claim 1, wherein the mapped multidimensional cube comprises a leave liabilities cube.

8. The analytics engine of claim 1, wherein the mapped multidimensional cube comprises a sales opportunities cube.

9. The analytics engine of claim 1, wherein the operations further comprise automatically adding the one or more mapped dimensions and associating the one or more mapped measures in response to startup of the analytics engine.

10. The analytics engine of claim 1, wherein the operations further comprise automatically adding the one or more mapped dimensions and associating the one or more mapped measures in response to an event, user input, or a combination thereof.

11. The analytics engine of claim 1, wherein members of at least one dimension of the first set of dimensions are static and wherein members of at least one mapped dimension are determined based on the mapped multidimensional cube during query execution.

12. A computer-readable storage device storing instructions that, when executed by a processor, cause the processor to perform operations comprising:

identifying a source fact table, wherein the source fact table includes a first set of dimensions and corresponds to a source multidimensional cube that is associated with a first set of measures;

identifying a mapped multidimensional cube, wherein the mapped multidimensional cube is associated with a second set of dimensions and a second set of measures;

adding, to the source fact table, one or more mapped dimensions corresponding to the second set of dimensions; and

associating, with the source multidimensional cube, one or more mapped measures corresponding to the second set of measures.

13. The computer-readable storage device of claim 12, wherein the operations further comprise:

receiving, from a computing device, a query identifying the source multidimensional cube, a mapped measure associated with the source multidimensional cube, and one or more classification values;

generating a cell set, wherein each cell of the cell set corresponds to a respective combination of the one or more classification values;

executing the mapped measure with respect to each cell of the cell set to generate one or more query execution results; and

sending the one or more query execution results to the computing device.