Systems and Methods for Providing Performance Metadata in Interest-Driven Business Intelligence Systems

• US 20140114909A1
• Filed: 10/22/2013
• Published: 04/24/2014
• Est. Priority Date: 10/22/2012
• Status: Active Grant

• Current Assignee: Workday Incorporated
• Original Assignee: Platfora Incorporated (Workday Incorporated)
• Inventors: Schuster, John, Ghani, Usman, Babcock, Brian, Rhim, Jenn, Eshelman, John, Schlampp, Peter
• Granted Patent: US 9,405,812 B2
• Time in Patent Office: Days
• US Class Current: 707/602
• CPC Class Codes: G06F 11/3006 where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems multiprogramming arrangements G06F9/46; allocation of resources G06F9/50
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06F 16/219 Managing data history or versioning querying versioned data G06F16/2474; querying temporal data G06F16/2477
• CPC Class Codes: G06F 16/2462 Approximate or statistical queries
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/27 Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/284 Relational databases

Abstract

Interest-driven business intelligence server systems that provide performance metadata are described. In the disclosed embodiments, an interest-driven business intelligence server system receives a report specification. The report specification includes at least reporting data requirement. The interest-driven business intelligence server determines performance metadata information for an interest-driven data pipeline that is utilized to generate reporting data based on the report specification. The performance metadata information for the interest-driven data pipeline is transmitted to an interest-driven user visualization system by the interest-driven business intelligence server system.

Claims

1. An interest-driven business intelligence server system, comprising:

a processor;

a memory connected to the processor and configured to store an interest-driven business intelligence application;

raw data storage configured to store raw data, where a portion of the raw data comprises unstructured data;

metadata storage configured to store data description metadata describing the raw data; and

report storage configured to store previously generated reports comprising previous reporting data and previous reporting data requirements;

wherein the interest-driven business intelligence application configures the processor to;

receive a report specification, where the report specification comprises at least one reporting data requirement;

determine performance metadata information for an interest-driven data pipeline that is utilized to generate reporting data based on the report specification; and

provide the performance metadata information for the interest-driven data pipeline to an interest-driven user visualization system.

2. The system of claim 1, wherein the performance metadata information for interest-driven data pipeline provided to the interest-driven user visualization system includes performance metadata for at least one of the raw data, the reporting data, and the source data of the interest-driven data pipeline.

3. The system of claim 1 wherein the performance metadata information for the interest-driven data pipeline provided to the interest-driven user visualization system includes historical performance metadata for the interest-driven data pipeline.

4. The system of claim 3 wherein the interest-driven business intelligence application configures the processor to retrieve the historical performance metadata from one of metadata accessible by the interest-driven business intelligence server system and a memory storing the historical performance metadata for the interest-driven data pipeline.

5. The system of claim of 1 wherein the performance metadata information provided to the interest-driven visualization system includes estimates of performance metadata for the interest-driven data pipeline.

6. The system of claim 5 wherein the interest-driven business intelligence application configures the processor to determine estimates of performance metadata for at least one of the raw data, the reporting data, and the source data in the interest-driven data pipeline that is utilized to generate reporting data based on the report specification.

7. The system of claim 6 wherein the interest-driven business intelligence application configures the processor to:

obtain a sample of the raw data needed to satisfy the reporting requirements;

determine performance metadata of the sample raw data; and

determine estimates of performance metadata for the raw data needed to satisfy the reporting requirements based on the determined performance metadata of the sample of raw data.

8. The system of claim 7 wherein:

the interest-driven business intelligence application obtains the sample of raw data by configuring the processor to;

generate a mini job that is an ETL processing job that extracts a sufficient amount to data provide an accurate sample of the raw data available;

provide the mini job to an distributed storage system; and

receive the sample of raw data from the distributed storage system in response to the mini job; and

the performance metadata for the sample of raw data includes performance metadata for the mini job and the estimates of the performance metadata includes estimates for an ETL processing job for obtaining raw data to satisfy the reporting requirements.

9. The system of claim 8 wherein:

the interest-driven business intelligence application determines estimates of performance metadata for the raw data satisfying the reporting data requirements by configuring the processor to retrieve historical performance metadata for the raw data satisfying the reporting data requirements; and

the historical information is used to determine the estimate of the performance metadata for the raw data satisfying the reporting data requirements.

10. The system of claim 7 wherein the interest driven data sharing application configures the processor to:

obtain the sample of raw data satisfying the reporting data requirements;

generate a sample of source data satisfying the reporting data requirements from the sample of raw data;

determine performance metadata for the sample of source data; and

determine estimates of performance metadata for the sample of source data satisfying the reporting requirements based on the determined performance metadata of the sample of source data.

11. The system of claim 10 wherein:

the interest-driven business intelligence application obtains the sample of source data by configuring the processor to;

apply required filters to the sample of raw data; and

apply required aggregations to the sample of raw data; and

the performance metadata includes performance metadata for the required aggregations and required filters.

12. The system of claim 11 wherein the performance metadata for the source data includes performance metadata for the required filters and the required aggregations.

13. The system of claim 11 wherein:

the interest-driven business intelligence application determines estimates of performance metadata for the source data satisfying the reporting data requirements by configuring the processor to retrieve historical performance metadata for source data satisfying the reporting data requirements; and

the historical information is used to determine the estimate of the performance metadata for the source data satisfying the reporting data requirements.

14. The system of claim 10 wherein the interest driven data sharing application configures the processor to:

obtain the sample of source data satisfying the reporting data requirements;

build a sample of reporting data satisfying the reporting data requirements from the sample of source data;

determine performance metadata for the sample of reporting data; and

determine estimates of performance metadata for the sample of reporting data satisfying the reporting requirements based on the determined performance metadata of the sample of source data.

16. The system of claim 1 wherein the interest-driven data pipeline includes transformation processes that transform a set of raw data into a set of reporting data and intermediate sets of data generated by the transformation processes.

15. The system of 14 wherein the interest-driven business intelligence application determines estimates of performance metadata for the reporting data satisfying the reporting data requirements by configuring the processor to:

retrieve historical performance metadata for the reporting data satisfying the reporting data requirements; and

wherein the historical performance metadata is used to determine the estimate of the performance metadata for the reporting data satisfying the reporting data requirements.

17. A method performed by an interest-driven business intelligence server system to provide performance metadata for an interest-driven data pipeline comprising:

receiving a report specification using an interest-driven business intelligence server system, where the report specification comprises at least one reporting data requirement;

determining performance metadata information for an interest-driven data pipeline that is utilized to generate reporting data based on the report specification wherein the performance metadata information includes at least one of estimates of performance metadata for the interest-driven data pipeline and historical performance metadata of the interest driven data pipeline; and

transmitting the performance metadata information for the interest-driven data pipeline to an interest-driven user visualization system using the interest-driven business intelligence server system.

18. The method of claim 17, further comprising:

obtaining a sample of the raw data needed to satisfy the reporting requirements using the interest-driven business intelligence server system;

determining performance metadata of the sample raw data using the interest-driven business intelligence server system; and

determining estimates of performance metadata for the raw data needed to satisfy the reporting requirements based on the determined performance metadata of the sample of raw data using the interest-driven business intelligence server system.

19. The method of claim 17, further comprising:

obtaining the sample of raw data satisfying the reporting data requirements using the interest-driven business intelligence server system;

generating a sample of source data satisfying the reporting data requirements from the sample of raw data using the interest-driven business intelligence server system;

determining performance metadata for the sample of source data using the interest-driven business intelligence server system; and

determining estimates of performance metadata for the sample of source data satisfying the reporting requirements based on the determined performance metadata of the sample of source data using the interest-driven business intelligence server system.

20. The method of claim 17, further comprising:

generating a mini job that is an ETL processing job that extracts a sufficient amount to provide an accurate sample of the raw data available using the interest-driven business intelligence server system;

providing the mini job to a distributed storage system using the interest-driven business intelligence server system; and

receiving the sample of raw data from the distributed storage system in response to the mini job using the interest-driven business intelligence server system;

wherein the performance metadata for the sample of raw data includes performance metadata for the mini job and the estimates of the performance metadata includes estimates for an ETL processing job for obtaining raw data to satisfy the reporting requirements.

21. The method of claim 20, further comprising retrieve historical performance metadata for the raw data satisfying the reporting data requirements, wherein the historical information is used to determine the estimate of the performance metadata for the raw data satisfying the reporting data requirements.

22. The method of claim 17, wherein the interest-driven data pipeline includes transformation processes that transform a set of raw data into a set of reporting data and intermediate sets of data generated by the transformation processes.

23. A method performed by an interest-driven business intelligence server system to provide metric data for an interest-driven data pipeline comprising:

receiving a report specification using an interest-driven business intelligence server system, where the report specification comprises at least one reporting data requirement;

determining performance metadata information for an interest-driven data pipeline that is utilized to generate reporting data based on the report specification wherein the performance metadata information includes estimates of performance metadata for the interest-driven data pipeline including performance metadata for raw data wherein the estimates of the performance metadata for the raw data are determined by;

generating a mini job that is an ETL processing job that extracts a sufficient amount to provide an accurate sample of the raw data available using the interest-driven business intelligence server system,

providing the mini job to a distributed storage system using the interest-driven business intelligence server system,

receiving the sample of raw data from the distributed storage system in response to the mini job using the interest-driven business intelligence server system,

determining performance metadata of the sample raw data using the interest-driven business intelligence server system wherein the performance metadata for the sample of raw data includes performance metadata for the mini job and the estimates of the performance metadata includes estimates for an ETL processing job for obtaining raw data to satisfy the reporting requirement,

determining estimates of performance metadata for the raw data needed to satisfy the reporting requirements based on the determined performance metadata of the sample of raw data using the interest-driven business intelligence server system; and

transmitting the performance metadata information for the interest-driven data pipeline to an interest-driven user visualization system using the interest-driven business intelligence server system.

24. An interest-driven business intelligence server system, comprising:

a processor;

a memory connected to the processor and configured to store an interest-driven business intelligence application;

raw data storage configured to store raw data, where a portion of the raw data comprises unstructured data;

metadata storage configured to store data description metadata describing the raw data; and

report storage configured to store previously generated reports comprising previous reporting data and previous reporting data requirements;

wherein the interest-driven business intelligence application configures the processor to;

receive a report specification, where the report specification comprises at least one reporting data requirement;

determine performance metadata information for an interest-driven data pipeline that is utilized to generate reporting data based on the report specification wherein the interest-driven data pipeline includes transformation processes that transform a set of raw data into a set of reporting data and intermediate sets of data generated by the transformation processes and wherein the performance metadata information for interest-driven data pipeline includes performance metadata for raw data, reporting data, and source data of the interest-driven data pipeline and wherein the performance metadata for the raw data by configuring the processor to;

generate a mini job that is an ETL processing job that extracts a sufficient amount to data provide an accurate sample of the raw data available,

provide the mini job to an distributed storage system,

receive the sample of raw data from the distributed storage system in response to the mini job,

determine performance metadata of the sample raw data; and

determine estimates of performance metadata for the raw data needed to satisfy the reporting requirements based on the determined performance metadata of the sample of raw data,

wherein the performance metadata for the sample of raw data includes performance metadata for the mini job and the estimates of the performance metadata includes estimates for an ETL processing job for obtaining raw data to satisfy the reporting requirements,

wherein the interest-driven business intelligence application determines estimates of performance metadata for the raw data satisfying the reporting data requirements by configuring the processor to retrieve historical performance metadata for the raw data satisfying the reporting data requirements, and

wherein the historical information is used to determine the estimate of the performance metadata for the raw data satisfying the reporting data requirements; and

provide the performance metadata information for the interest-driven data pipeline to an interest-driven user visualization system.