IP Library Granted Patent US 10,614,091
Granted Patent B1
US 10,614,091 · App. 15/279,839 · Granted Apr 7, 2020

Warehouse based reporting and operational reporting integration

Inventors: Rahul Kapoor (Sunnyvale, CA); Gaurav Rewari (Cupertino, CA); Aravind Sridharan (San Jose, CA); Sadanand Sahasrabudhe (Rockville, MD); Florian Schouten (Wayland, MA)
Assignee: Numerify, Inc.
G06F16/254G06F16/283
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Quick Facts
Patent No.
US 10,614,091
App. No.
15/279,839
Granted
Apr 7, 2020
Kind
B1
Abstract

Approaches for integrating an operational reporting system with a warehouse based reporting system. The operational reporting system and the warehouse based reporting system may be offered and supported by different vendors, and so may be deployed in different clouds or as separate product installations in case of on-premise software, or these systems may be offered and supported by a single vendor, and so may be deployed in the same cloud or as part of a common product installation in case of on-premise software. The integrated system uses a common or consistent dimensional model to link related measures of the operational reporting system and the warehouse based reporting system, which allows for analysis of real time content with historical and cross subject perspective provided alongside in the same interface. The integration also facilitates trend analysis and predictive analytics in real time.

Claims (52)

1. One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes automatic integration of an operational reporting system and a warehouse based reporting system that are supported by two separate vendors using a common dimensional model and separate data processing infrastructure, by performing the steps of:

querying said operational reporting system for model and mapping information extraction;

automatically enforcing consistency between a data model of said operational reporting system and a dimensional data model of said warehouse based reporting system by aligning said dimensional data model of said warehouse based reporting system with said data model of said operational reporting system using software aids, wherein said software aids query said dimensional data model of said warehouse based reporting system and said data model of said operational reporting system for model definitions and mappings of metrics to source elements tracked using lineage capabilities to identify equivalent model elements for model alignment by comparison of their definitions;

automatically ensuring consistency of (i) data extraction methods between said operational reporting system and said warehouse based reporting system, (ii) timestamping, and timezones of data associated with said operational reporting system and said warehouse based reporting system, and (iii) collations across said operational reporting system and said warehouse based reporting system, upon determining that populating the data in a common or consistent dimensional model occurs;

automatically analyzing real time content provided by said operational reporting system with historical content and cross subject perspective provided by said warehouse based reporting system; and

automatically enabling predictions for said real time content based on said common or consistent dimensional model that links said real time content of said operational reporting system with historical content and predictive models of said warehouse based reporting system.

2. The one or more non-transitory computer readable storage mediums storing one or more sequences of instructions of claim 1 , which when executed by one or more processors further causes:

automatic detection of one or more data discrepancies, between same metrics of said operational reporting system and said warehouse based reporting system, caused due to (a) different data refresh times of the data associated with said operational reporting system and said warehouse based reporting system, and (b) skipping data quality correction on the data associated with said operational reporting system for efficiency;

automatic elimination of said data discrepancies caused due to different data refresh times by identifying using lineage, tables including logically connected tables, based on which said metrics are computed, and incrementally refreshing the said tables using code generated incremental refresh jobs to have the same data in both said operational reporting system and said warehouse based reporting system; and

automatic elimination of said data discrepancies caused due to skipped data quality transforms by incorporating said data quality transforms for said operational reporting system.

3. The one or more non-transitory computer readable storage mediums storing one or more sequences of instructions of claim 2 , which when executed by one or more processors further causes:

automatic identification of relevant trends from said data discrepancies by comparing metric values of said operational reporting system with current and historical values of same metrics in said warehouse based reporting system; and

automatic generation of alerts upon determining that said data discrepancies exceed a predefined value, or an auto identified threshold value.

4. The one or more non-transitory computer readable storage mediums storing one or more sequences of instructions of claim 1 , which when executed by one or more processors further causes displaying said relevant trends using business intelligence charts.

5. An integrated system that integrates a warehouse based reporting system with an operational reporting system using a common dimensional model, said integrated system comprising:

a memory that stores a database and a first set of modules;

a processor that executes said first set of modules, wherein said first set of modules comprises;

a rendering module that automatically analyzes real time content provided by said operational reporting system with historical content and cross subject perspective provided by said warehouse based reporting system;

a predictive analysis module that automatically enables predictions for said real time content based on said common or consistent dimensional model that links said real time content of said operational reporting system with historical content and predictive models of said warehouse based reporting system;

a data discrepancy detection module that automatically detects one or more data discrepancies, between same metrics of said operational reporting system and said warehouse based reporting system, caused due to (a) different data refresh times of the data associated with said operational reporting system and said warehouse based reporting system, and (b) skipping data quality correction on the data associated with said operational reporting system for efficiency;

a relevant trend identification module that automatically identifies relevant trends from said data discrepancies by comparing metric values of said operational reporting system with current and historical values of the same metrics in said warehouse based reporting system;

a proactive alerting module that automatically generates alerts upon determining that said data discrepancies exceed a predefined value, or an auto identified threshold value;

a data discrepancy elimination module that automatically eliminates said data discrepancies caused due to different data refresh times by identifying using lineage, tables including logically connected tables, based on which said metrics are computed, and incrementally refreshing the said tables, using code generated incremental refresh jobs to have the same data in both said operational reporting system and said warehouse based reporting system; and

a data correction module that automatically eliminates said data discrepancies caused due to skipped data quality transforms by incorporating said data quality transforms for said operational reporting system.

6. The integrated system as claimed in claim 5 , wherein upon determining that said operational reporting system and said warehouse based reporting system are supported by two separate vendors using a common dimensional model and separate data processing infrastructure, said integrated system additionally comprises:

an operational reporting system analysis module that queries an operational reporting system for model and mapping information extraction; and

a model and mapping consistency validation module that automatically enforces consistency between a data model of said operational reporting system and a dimensional data model of said warehouse based reporting system by aligning said dimensional data model of said warehouse based reporting system with said data model of said operational reporting system using software aids, wherein said software aids query said dimensional data model of said warehouse based reporting system and said data model of said operational reporting system for model definitions and mappings of metrics to source elements tracked using lineage capabilities to identify equivalent model elements for model alignment by comparison of their definitions.

7. The integrated system as claimed in claim 5 , wherein upon determining that (i) said operational reporting system is supported by a warehouse vendor using a common dimensional data model with separate data processing infrastructure, or (ii) said operational reporting system and said warehouse based reporting system are supported by two separate vendors using a common dimensional model and separate data processing infrastructure, said integrated system additionally comprises a parameters consistency enforcement module that automatically ensures consistency of (i) data extraction methods between said operational reporting system and said warehouse based reporting system, (ii) timestamping, and timezones of data associated with said operational reporting system and said warehouse based reporting system, and (iii) collations across said operational reporting system and said warehouse based reporting system upon determining that populating the data in a common or consistent dimensional model occurs.

8. The integrated system as claimed in claim 5 , wherein upon determining that said operational reporting system is supported by a warehouse vendor using a common dimensional data model with a common or separate data processing infrastructure, said integrated system additionally comprises:

an altering existing warehouse jobs module that automatically ensures that modified jobs are generated for near real time data access and real time data access for a subset of warehouse tables upon determining that (i) ensuring logically related group of warehouse tables are updated together to avoid any inconsistencies with selective updating, and (ii) tracking dropped transforms which may cause potential data discrepancies; and

a real time data capture module for capturing source data changes in real time for said operational reporting system.

9. One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes automatic integration of a warehouse based reporting system, and an operational reporting system that is supported by a warehouse vendor using a common dimensional data model and common data processing infrastructure for said operational reporting system and said warehouse based reporting system, by performing the steps of:

automatically ensuring that modified jobs are generated for near real time data access and real time data access for a subset of warehouse tables upon determining that (i) ensuring logically related group of warehouse tables are updated together to avoid any inconsistencies with selective updating, and (ii) tracking dropped transforms which may cause potential data discrepancies;

automatically capturing source data changes in real time for said operational reporting system;

automatically analyzing real time content provided by said operational reporting system with historical content and cross subject perspective provided by said warehouse based reporting system;

automatically enabling predictions for said real time content based on a common or consistent dimensional model that links said real time content of said operational reporting system with historical content and predictive models of said warehouse based reporting system;

automatically detecting one or more data discrepancies between said operational reporting system and said warehouse based reporting system caused due to (a) different data refresh times of the data associated with said operational reporting system and said warehouse based reporting system, and (b) skipping data quality correction on the data associated with said operational reporting system for efficiency;

automatically identifying relevant trends from said data discrepancies by comparing metric values of said operational reporting system with current and historical values of the same metrics in said warehouse based reporting system;

automatically generating alerts upon determining that said data discrepancies exceed a predefined value, or an auto identified threshold value;

automatically eliminating said data discrepancies caused due to different data refresh times by identifying using lineage, tables including logically connected tables, based on which said metrics are computed and incrementally refreshing the said tables, using code generated incremental refresh jobs to have the same data in both said operational reporting system and said warehouse based reporting system; and

automatically eliminating said data discrepancies caused due to skipped data quality transforms by incorporating said data quality transforms for said operational reporting system.

10. One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes automatic integration of a warehouse based reporting system and an operational reporting system that is supported by a warehouse vendor using a common dimensional data model and separate data processing infrastructure for said operational reporting system and said warehouse based reporting system, by performing the steps of:

automatically ensuring that modified jobs are generated for near real time data access and real time data access for a subset of warehouse tables upon determining that (i) ensuring logically related group of warehouse tables are updated together to avoid any inconsistencies with selective updating, and (ii) tracking dropped transforms which may cause potential data discrepancies;

automatically ensuring consistency of (i) data extraction methods between said operational reporting system and said warehouse based reporting system, (ii) timestamping, and timezones of data associated with said operational reporting system and said warehouse based reporting system, and (iii) collations across said operational reporting system and said warehousing based reporting system upon determining that populating the data in a common or consistent dimensional model occurs;

automatically capturing source data changes in real time for said operational reporting system;

automatically analyzing said real time content provided by said operational reporting system with historical content and cross subject perspective provided by said warehousing based reporting system;

automatically enabling predictions for real time content based on said common or consistent dimensional model that links said real time content of said operational reporting system with historical content and predictive models of said warehousing based reporting system;

automatically detecting one or more data discrepancies between said operational reporting system and said warehouse based reporting system caused due to (a) different data refresh times of the data associated with said operational reporting system and said warehouse based reporting system, and (b) skipping data quality correction on the data associated with said operational reporting system for efficiency;

automatically identifying relevant trends from said data discrepancies by comparing metric values of said operational reporting system with current and historical values of the same metrics in said warehousing based reporting system;

automatically generating alerts upon determining that said data discrepancies exceed a predefined value, or an auto identified threshold value;

automatically eliminating said data discrepancies caused due to different data refresh times by automatically identifying using lineage, tables including logically connected tables, based on which said metrics are computed, and incrementally refreshing the said tables, using code generated incremental refresh jobs to have the same data in both said operational reporting system and said warehouse based reporting system; and

automatically eliminating said data discrepancies caused due to skipped data quality transforms by incorporating said data quality transforms for said operational reporting system.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 8, 2021
From: NUMERIFY, INC.
To: DIGITAL.AI SOFTWARE, INC.
Reel/Frame 055859/0189 →
SECURITY INTEREST Recorded Feb 10, 2021
From: VERSIONONE, INC.; DIGITAL.AI SOFTWARE, INC.; ARXAN TECHNOLOGIES, INC.; NUMERIFY, INC.; XEBIALABS, INC.
To: MIDCAP FINANCIAL TRUST
Reel/Frame 055277/0043 →
CHANGE OF ADDRESS Recorded Dec 20, 2017
From: NUMERIFY, INC.
To: NUMERIFY, INC.
Reel/Frame 044957/0526 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 3, 2017
From: KAPOOR, RAHUL; REWARI, GAURAV; SRIDHARAN, ARAVIND; SAHASRABUDHE, SADANAND; SCHOUTEN, FLORIAN
To: NUMERIFY, INC.
Reel/Frame 041167/0047 →
Cited By (4)
US 12,216,650 US 12,216,651 US 12,405,962 US 12,566,763