IP Library Granted Patent US 11,526,518
Granted Patent B2
US 11,526,518 · App. 15/712,917 · Granted Dec 13, 2022

Data reporting system and method

Inventors: John Payne (Seattle, WA); Yung Haw Wang (Seattle, WA); Mohan Rao Varthakavi (Sammamish, WA); Jose Kunnackal John (Redmond, WA); Santosh Kalki (Sammamish, WA); Mukul Vijay Karnik (Redmond, WA); Jared Scott Lundell (Mercer Island, WA)
Assignee: Amazon Technologies, Inc.
G06F16/24573G06Q30/016G06Q40/12G06Q10/10
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Quick Facts
Patent No.
US 11,526,518
App. No.
15/712,917
Granted
Dec 13, 2022
Kind
B2
Abstract

A data analysis system determines characteristics of a data set such as statistical measures, analytical insights, data trends, or relationships with other data sets. The system determines a level of importance for each determined characteristic using metadata associated with the data set, and, in some cases, user preferences provided by the user. Such metadata may include descriptive names, data types, and data characteristics of the data set and of data elements within the data set.

Claims (66)

1. A method, comprising:

obtaining, at a computer system, a dataset associated with a customer, and metadata of the dataset, provided with the dataset, wherein the metadata comprises descriptive information for at least some data of the dataset, at least a portion of the descriptive information corresponding to structured data comprised in the dataset;

analyzing, using a processor of the computer system, the dataset to identify a set of characteristics of the dataset, the set of characteristics comprising statistical values calculated based at least in part on the dataset;

selecting a subset of the characteristics based at least in part on at least one score associated with the set of characteristics, the at least one score determined at least based on at least one user preference associated with the customer and at least a portion of the metadata; and

presenting the subset of the characteristics to the customer with a visualization of the dataset.

2. The method of claim 1 , wherein:

the metadata associated with the dataset includes a natural language name for a data element of the dataset; and

the subset of the characteristics are presented to the customer in a natural language format.

3. The method of claim 1 , wherein the set of characteristics includes a relationship with another dataset, an outlier data element in the dataset, or a data trend of the dataset.

4. The method of claim 1 , further comprising:

determining a base score for each characteristic in the set of characteristics, the base score based at least in part on a type of each characteristic; and

producing the at least one score for each characteristic based at least in part on the base score of each characteristic and the at least one user preference, the at least one user preference related to each characteristic.

5. The method of claim 1 , wherein the descriptive information corresponding to the structured data comprised in the dataset identifies at least a portion of a formatting for the structured data.

6. A system comprising:

one or more processors; and

a memory storing instructions that, as a result of being executed by the one or more processors, cause the system to:

obtain a dataset;

analyze the dataset to identify a set of characteristics of the dataset;

select a subset of the characteristics based at least in part on at least one score associated with the set of characteristics, the at least one score determined at least based on at least one user preference and at least a portion of metadata, wherein the metadata is provided with the dataset and the metadata comprises descriptive information for at least some data of the dataset; and

provide the subset of the characteristics to the user.

7. The system of claim 6 , wherein:

the dataset is data provided by the user; and

the system provides the subset of the characteristics to the user.

8. The system of claim 7 , wherein the instructions, as a result of being executed by the one or more processors, further cause the system to provide the subset of the characteristics to the user by at least:

generating a hypertext markup language web page that describes the subset of the characteristics;

sending the hypertext markup language web page to a client computer system; and

causing the client computer system to display the hypertext markup language web page in a web browser.

9. The system of claim 6 , wherein the instructions, as a result of being executed by the one or more processors, further cause the system to:

determine a base score for each characteristic in the set of characteristics, the base score based at least in part on a type of each characteristic, the base score for at least one of the characteristics in the set of characteristics associated with the at least one score.

10. The system of claim 9 , wherein the instructions, as a result of being executed by the one or more processors, further cause the system to:

acquire preferences of the user for the set of characteristics;

determine an adjusted score for each characteristic based at least in part on the preferences; and

select the subset of the characteristics from the set of characteristics based at least in part on at least one of the adjusted scores, wherein the at least one of the adjusted scores comprises the at least one score.

11. The system of claim 6 , wherein the instructions, as a result of being executed by the one or more processors, further cause the system to acquire the metadata by at least:

determining the metadata based at least in part on a name of the dataset; and

determining the metadata based at least in part on a name of a data field of the dataset.

12. The system of claim 6 , wherein the subset of the characteristics that are provided to the user include a characteristic of the dataset presented in the form of a natural language insight describing the dataset.

13. The system of claim 6 , wherein the subset of the characteristics that are provided to the user include a relationship with another dataset.

14. The system of claim 6 , wherein the descriptive information identifies at least a portion of a formatting for the data of the dataset.

15. A non-transitory computer-readable storage medium with executable instructions stored thereon that, as a result of being executed by one or more processors of a computer system, cause the computer system to at least:

obtain a dataset;

analyze the dataset to identify a set of characteristics of the dataset;

select a subset of the characteristics based at least in part on at least one score associated with the set of characteristics, the at least one score determined at least based on at least one user preference associated with the customer and at least a portion of metadata, wherein the metadata is provided with the dataset and the metadata comprises descriptive information for the dataset; and

provide the subset of the characteristics to the user.

16. The non-transitory computer-readable storage medium of claim 15 , wherein:

the dataset is data uploaded by the user to the computer system from a client computer system via a computer network; and

the system provides the subset of the characteristics to the user.

17. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further comprise instructions that, as a result of being executed by the one or more processors, cause the computer system to:

identify a name for each data field in the dataset;

identify a data type for each data field of the dataset;

generate a score for each characteristic of the dataset based at least in part on the name and the type of each data field associated with each characteristic, at least one of the generated scores comprising the at least one score; and

select the subset of the characteristics based at least in part on the score of each characteristic.

18. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further comprise instructions that, as a result of being executed by the one or more processors, cause the computer system to:

determine a level of confidence for each characteristic in the set of characteristics; and

select the subset of the characteristics based at least in part on the level of confidence of each characteristic.

19. The non-transitory computer-readable storage medium of claim 18 , wherein:

the subset of the characteristics includes a characteristic that identifies an outlier of the dataset; and

the level of confidence for the characteristic that identifies the outlier is a value related to the degree of the outlier.

20. The non-transitory computer-readable storage medium of claim 18 , wherein:

the subset of the characteristics includes a characteristic that identifies a relationship with another dataset; and

the level of confidence for the characteristic that identifies a relationship is a value related to the degree of the relationship between the dataset and the other dataset.

21. The non-transitory computer-readable storage medium of claim 20 , wherein the relationship to the other dataset is a correlation with the other dataset or a period-over-period comparison with the other dataset.

22. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further comprise instructions that, as a result of being executed by the one or more processors, cause the computer system to:

generate a document that describes the subset of the characteristics; and

send the document to a client computer system.

23. The non-transitory computer-readable storage medium of claim 15 , wherein the descriptive information identifies at least a portion of a formatting for the data of the dataset.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 22, 2017
From: PAYNE, JOHN; WANG, YUNG HAW; VARTHAKAVI, MOHAN RAO; KUNNACKAL JOHN, JOSE; KALKI, SANTOSH; KARNIK, MUKUL VIJAY; LUNDELL, JARED SCOTT
To: AMAZON TECHNOLOGIES, INC.
Reel/Frame 043666/0287 →
Continuity (1)
Related Publication 20190095499A1 · Mar 28, 2019