Data center analytics and dashboard

• US 9,613,322 B2
• Filed: 04/02/2014
• Issued: 04/04/2017
• Est. Priority Date: 04/02/2013
• Status: Active Grant

• Current Assignee: Contiem Incorporated
• Original Assignee: Orbis Technology
• Inventors: Clark, David, Blenkhorn, Ari
• Primary Examiner(s): CHEN, ALAN S
• Application Number:
  US14/243,503
• Publication Number:
  US 20140297569A1
• Time in Patent Office: 1,098 Days
• Field of Search: None
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

A method and system to evaluate data efficacy across an enterprise is disclosed. The method includes the step of indexing a set of data sources that include at least one of structured and unstructured data artifacts. The method further includes accessing the indexing on the one or more data sources with a computer. The method further includes the step of generating a plurality of analytics about the data sources based on the indexing, wherein the analytics include a plurality of: a document originality analytic, a corpus storage volume analytic, a data source ingest analytic, a document type analytic, and an analysis analytic. The method further includes displaying, on a display device, an interactive visualization of results based on the analytics, wherein the visualization comprises at least one of: a histogram, a graph, a timeline, a panel, a list, a chart, a popup, and a table.

Claims

1. A computer-implemented method to evaluate data efficacy across an enterprise, comprising:

indexing a set of data sources that comprise at least one of structured and unstructured data artifacts;

accessing the indexing on one or more data sources with a computer;

generating with a computer, a plurality of analytics about the data sources based on the indexing, wherein the analytics generated by the computer include a plurality of;

a document originality analytic that evaluates originality of data within a corpus of documents;

a corpus storage volume analytic that provides metrics based on a relative value of data based on facts extracted from the one or more data sources versus facts inferred from the one or more data sources using at least one of models, logic and rules;

a data source ingest analytic that identifies growth in at least one of ingest rates and update rates;

a document type analytic that uses document metadata to analyze types of documents in the corpus of documents and provide metrics depicting a number of documents of each of the types in the corpus of documents; and

an analysis analytic that identifies top entity-to-entity relationships across a set of the one or more data sources; and

displaying, on a display device connected to the computer, an interactive visualization of results based on the analytics, wherein the visualization on the display device includes at least one of;

a histogram, a graph, a timeline, a panel, a chart, a popup, a list, and a table.

2. The method of claim 1, wherein the analytics are further based on one or more analytics clients associated with the one or more data sources.

3. The method of claim 2, wherein the interactive visualization further includes drill-down capabilities based on at least one of the analytics clients and the indexing.

4. The method of claim 1, wherein the plurality of analytics includes the document originality analytic, and wherein said indexing includes:

indexing the data sources based on at least one of the following to generate the document originality analytic;

exact text matching, similar fact matching, and data source and data artifact metadata, and

depicting, in the visualization, an original number of sentences for each type of data artifact.

5. The method of claim 1, wherein the plurality of analytics includes the corpus storage volume analytic, further comprising:

indexing the data artifacts of the data sources using at least one of one or more models and logic to generate the corpus storage volume analytic;

extracting one or more of the facts from the data artifacts of the data sources;

inferring one or more of the facts from the data artifacts of the corpus; and

depicting, in the visualization, the one or more facts extracted from the data artifacts, the one or more facts inferred from the data artifacts, a total disk storage required for each of the one or more facts extracted from the data artifacts, and a total disk storage required for each of the facts inferred from the data artifacts.

6. The method of claim 1, wherein the plurality of analytics includes the data source ingest analytic, further comprising:

deriving metadata at at least one of a time of upload and ingest of the data sources, wherein the step of indexing further includes indexing the data source and data artifact metadata, and

determining growth in at least one of the ingest rates and the update rates based on the indexed metadata to generate the data source ingest analytic.

7. The method of claim 1, wherein the plurality of analytics includes the document type analytic, further comprising:

identifying a type of data artifacts in the data sources based on metadata associated with each data artifact to generate the document type analytic.

8. The method of claim 1, wherein the plurality of analytics includes the analysis analytic, further comprising:

determining, using at least one of one or more models and logic, as well as entities, relationships, sentences, and derived content in the data artifacts to generate the analysis analytic;

generating statistics on the entities, relationships, sentences, and derived content across the data artifacts, wherein the visualization further includes a depiction of the statistics, such as top entities, top relationships, top documents based on the derived content, and top sentences.

9. The method of claim 1, wherein the one or more data sources comprise at least one of a large-scale cloud based data source.

10. A system to evaluate data efficacy across an enterprise, comprising:

a processor;

a display device coupled to said processor;

one or more non-transitory computer memories coupled to said processor storing program instructions executable by said processor to implement a data center analytics and dashboard configured to;

access a set of data sources over a communications network that comprise at least one of structured and unstructured data artifacts;

index the set of data sources;

generate a plurality of analytics about the data sources based on the indexing, wherein the analytics include a plurality of;

a document originality analytic that evaluates originality of data within a corpus of documents;

a corpus storage volume analytic that provides metrics based on a relative value of data based on facts extracted from the data sources versus facts inferred from the data sources using at least one of models, logic and rules;

a data source ingest analytic that identifies growth in at least one of ingest rates and update rates;

a document type analytic that uses document metadata to analyze types of documents in the corpus of documents and provide metrics depicting a number of documents of each of the types in the corpus of documents; and

an analysis analytic that identifies top entity-to-entity relationships across a set of the data sources; and

display, on said display device, an interactive visualization of results based on the analytics, wherein the visualization comprises at least one of;

a histogram, a graph, a timeline, a panel, a list, a chart, a popup, and a table.

11. The system of claim 10, wherein the analytics may further be based on analytics clients associated with one or more of the data sources.

12. The system of claim 11, further comprising an input device, wherein said processor is further configured to:

respond to inputs from said input device to display the interactive visualization of results with drill-down capabilities, wherein the drill-down capabilities are based on one or more analytics from at least one of the analytics clients and the indexing.

13. The system of claim 10, wherein the plurality of analytics includes the document originality analytic and said processor is further configured to:

index the data sources based on at least one of the following to generate said document originality analytic;

exact text matching, similar fact matching, and data source and data artifact metadata, and,

depict, in the visualization on said display device, an original number of sentences for each type of data artifact.

14. The system of claim 10, wherein the plurality of analytics includes the corpus storage analytic and said processor is further configured to:

index the data artifacts of the data sources, as part of said indexing, using at least one of one or more models and logic to generate the corpus storage volume analytic;

extract one or more of the facts from the data artifacts of said corpus;

infer one or more of the facts from the data artifacts of said corpus; and

depict, in said visualization displayed on said display device, the one or more facts extracted from the data artifacts, the one or more facts inferred from the data artifacts, a total disk storage required for each of the one or more facts extracted from the data artifacts, and a total disk storage required for each of the facts inferred from the data artifacts.

15. The system of claim 10, wherein the plurality of analytics includes the data source ingest analytic and said processor is further configured to:

derive metadata at at least one of a time of upload and ingest of the data sources and the data artifacts;

index the derived metadata; and

determine growth in at least one of the ingest rates and the update rates based on the indexed metadata to generate the data source ingest analytic.

16. The system of claim 10, wherein the plurality of analytics includes the document type analytic and said processor is further configured to:

identify a type of the data artifacts in the data sources based on metadata associated with each of the data artifacts to generate said document type analytic.

17. The system of claim 10, wherein the plurality of analytics includes an analysis analytic and said processor is further configured to:

determine, using at least one of one or more models and logic, as well as entities, relationships, sentences, and derived content in the data artifacts to generate said analysis analytic; and

generate statistics on the determined entities, relationships, sentences, and derived content across the data artifacts, wherein the visualization further comprises a depiction of the statistics, such as top entities, top relationships, top data artifacts based on the derived content, and top sentences.

18. The system of claim 10, wherein one or more of the data sources comprise at least one of a large-scale based data source.