SYSTEMS, METHODS, AND APPARATUSES FOR IMPLEMENTING CROSS-ORGANIZATIONAL PROCESSING OF BUSINESS INTELLIGENCE METRICS

• US 20140074558A1
• Filed: 09/11/2013
• Published: 03/13/2014
• Est. Priority Date: 09/12/2012
• Status: Active Grant

• Current Assignee: Salesforce.com, Inc.
• Original Assignee: Salesforce.com, Inc.
• Inventors: Tamm, Steven, Jain, Samarpan
• Granted Patent: US 10,460,270 B2
• Time in Patent Office: Days
• US Class Current: 705/7.36
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals

Abstract

In accordance with disclosed embodiments, there are provided methods, systems, and apparatuses for implementing cross-organizational processing of business intelligence metrics including, for example, means for scheduling a time for metrics collection from databases of a host organization; generating one or more messages and associated parameters to implement the metrics collection at the host organization; enqueuing the one or more messages and associated parameters for processing by the host organization; dequeuing the one or more messages and associated parameters into the host organization for processing, wherein the processing is to output the metrics collection into an intermediate table; capturing the metrics collection output via the processing at the intermediate table; and exposing the intermediate table to metrics queries. Other related embodiments are disclosed.

Claims

1. A method in a host organization, wherein the method comprises:

scheduling a time for metrics collection from databases of the host organization;

generating one or more messages and associated parameters to implement the metrics collection at the host organization;

enqueuing the one or more messages and associated parameters for processing by the host organization;

dequeuing the one or more messages and associated parameters into the host organization for processing, wherein the processing is to output the metrics collection into an intermediate table;

capturing the metrics collection output via the processing at the intermediate table; and

exposing the intermediate table to metrics queries.

2. The method of claim 1:

wherein scheduling the time for metrics collection comprises scheduling a metrics collection job at a specified periodicity; and

wherein the metrics collection job iterates at the specified periodicity.

3. The method of claim 2, wherein the specified periodicity is selected from one of a daily periodicity, a weekly periodicity, a bi-weekly periodicity, a monthly periodicity, a quarterly periodicity, and a yearly periodicity.

4. The method of claim 1, further comprising:

triggering the metrics collection at the time scheduled, wherein triggering the metrics collection comprises at least (i) generating one or more messages and associated parameters to implement the metrics collection and (ii) enqueuing the one or more messages and associated parameters for processing.

5. The method of claim 1, further comprising:

determining a granularity required to implement the metrics collection, the granularity being selected from one of a per-user, a per-tenant, a per-organization, a per-node, per-partition, or a per-database granularity; and

wherein generating one or more messages and associated parameters comprises generating the one or more messages for the metrics collection at the determined granularity.

6. The method of claim 1, wherein dequeuing the one or more messages and associated parameters into the host organization comprises:

dequeuing the one or more enqueued messages from a message queue; and

releasing the one or more messages and associated parameters for immediate processing.

7. The method of claim 1, wherein dequeuing the one or more messages and associated parameters into the host organization for processing comprises:

releasing a plurality of messages for processing in parallel by releasing at least one message to each of a plurality of nodes, partitions, or databases;

wherein the at least one message is to process on a per-node, per-partition, or per-database basis concurrently within the host organization; and

capturing the metrics collection output via the concurrent processing at the intermediate table.

8. The method of claim 7:

wherein the concurrent processing of the at least one message on a per-node, per-partition, or per-database basis generates related metrics collection output from each of the nodes, partitions, or databases respectively; and

wherein the method further comprises joining the related metrics collection output during insertion into the intermediate table.

9. The method of claim 1:

wherein the one or more messages and associated parameters are implemented via a bulk processing database call.

10. The method of claim 9, wherein capturing the metrics collection output via the processing at the intermediate table comprises specifying a BULK COLLECT INTO call for the processing and specifying the intermediate table as a target repository for the metrics collection output.

11. The method of claim 1, further comprising:

monitoring workload of the host organization; and

wherein dequeuing the one or more messages and associated parameters into the host organization for processing comprises releasing the one or more messages for immediate processing when the workload of the host organization is below a threshold.

12. The method of claim 11, further comprising:

processing real-time transaction requests at the host organization concurrently with the one or more messages and associated parameters to implement the metrics collection; and

prioritizing the real-time transaction requests over the one or more messages and associated parameters to implement the metrics collection.

13. The method of claim 1:

wherein capturing the metrics collection output via the processing at the intermediate table comprises capturing aggregation data at the intermediate table;

wherein the aggregation data of the intermediate table is abstracted from underlying records of the database upon which the aggregation data is based.

14. The method of claim 1:

wherein the databases of the host organization store underlying records on behalf of customer organizations, the underlying records having sensitive data stored therein; and

wherein the intermediate table stores the metrics collection output as aggregation data separate and distinct from the databases of the host organization, wherein the intermediate table is void of the underlying records having sensitive data stored therein.

15. The method of claim 14:

wherein the underlying records of the databases having sensitive data stored therein include at least one of HIPAA (Health Insurance Portability and Accountability Act) protected data;

Sarbanes-Oxley Act (SOX) protected data;

proprietary sales data;

proprietary financial data;

proprietary trade-secret data; and

government classified data; and

wherein the aggregation data is void of the sensitive data and includes metadata, metrics, and statistics.

16. The method of claim 1:

wherein the intermediate table comprises a queryable data repository common to a plurality of tenants of a multi-tenant database operated by the host organization;

wherein the databases of the host organization service database queries and do not service metrics queries; and

wherein the intermediate table services the metrics queries and does not service database queries.

17. The method of claim 1, wherein exposing the intermediate table to metrics queries comprises:

exposing a Business Intelligence (BI) Metrics Application Programming Interface (API) to users of the host organization;

wherein the BI Metrics API receives metrics queries for execution against the intermediate table; and

wherein the BI Metrics API returns metrics query responses responsive to the metrics queries.

18. The method of claim 1, wherein the metrics collection output captured via the intermediate table is tagged with time and/or date information specifying when the metrics collection output was captured.

19. The method of claim 1, wherein the metrics collection output captured via the intermediate table is associated with a customer organization ID column identifying which one among a plurality of customer organizations of the host organization is associated with any metric, statistic, or metadata present within the metrics collection output captured by the intermediate table.

20. The method of claim 19, further comprising:

receiving a metrics query; and

returning metrics query results from the intermediate table having metrics, statistics, and/or metadata associated with multiple customer organizations according to the customer organization ID column.

21. The method of claim 1:

wherein the databases of the host organization prohibit cross-organizational database queries having a query scope that exceeds a single individual customer organization; and

wherein the intermediate table is queryable via metrics queries having a query scope that exceeds a single individual customer organization.

22. The method of claim 21:

wherein a user of the host organization is restricted to metrics queries having a query scope that is limited to a single individual customer organization to which the user belongs; and

wherein system administrators of the host organization are enabled to perform metrics queries having a query scope that exceeds a single individual customer organization via a restricted administrative interface for the system administrators.

23. The method of claim 1, wherein exposing the intermediate table to metrics queries comprises:

exposing each of a plurality of objects within the intermediate table having aggregation data stored therein using a logical presentation, wherein each of the plurality of objects operates within a logical context of a particular column'"'"'s meaning to a given metric being queried.

24. The method of claim 1:

wherein the host organization implements the method via computing architecture of the host organization including at least a processor and a memory;

wherein a user interface operates at a user client device remote from the host organization and communicatively interfaces with the host organization via a public Internet; and

wherein the host organization operates as a cloud based service provider to the user client device.

25. The method of claim 24, wherein the host organization provides a multi-tenant database system via the databases and the computing architecture of the host organization, the multi-tenant database system having elements of hardware and software that are shared by a plurality of separate and distinct customer organizations, each of the separate and distinct customer organizations being remotely located from the host organization.

26. Non-transitory computer readable storage media having instructions stored thereon that, when executed by a processor in a host organization, the instructions cause the host organization to perform operations comprising:

scheduling a time for metrics collection from databases of the host organization;

generating one or more messages and associated parameters to implement the metrics collection at the host organization;

enqueuing the one or more messages and associated parameters for processing by the host organization;

dequeuing the one or more messages and associated parameters into the host organization for processing, wherein the processing is to output the metrics collection into an intermediate table;

capturing the metrics collection output via the processing at the intermediate table; and

exposing the intermediate table to metrics queries.

27. A system comprising:

a processor and a memory to execute instructions at the system;

databases having data records stored therein;

a scheduler to schedule a time for metrics collection from the databases;

a query builder to generate queries based on messages and associated parameters required to implement the metrics collection;

a message queue to enqueue the one or more messages and associated parameters for processing via the system;

a message handler to de-queue the one or more messages and associated parameters into the system for processing, wherein the processing is to output the metrics collection;

an intermediate table to capture the metrics collection output pursuant to the processing; and

an Application Programming Interface to expose the intermediate table to metrics queries.

28. The system of claim 27, further comprising:

a web-server to receive metrics queries from a plurality of customer organizations, wherein the metrics queries are to be passed to the API for execution against the intermediate table;

wherein the plurality of customer organizations communicably interface with the system via a network; and

wherein each customer organization is an entity selected from the group consisting of;

a separate and distinct remote organization, an organizational group within the host organization, a business partner of the host organization, or a customer organization that subscribes to cloud computing services provided by the host organization.