Database query builder

• US 9,798,748 B2
• Filed: 12/31/2012
• Issued: 10/24/2017
• Est. Priority Date: 06/19/2008
• Status: Active Grant

• Current Assignee: BioFortis, Inc. (IQVIA Holdings, Inc.)
• Original Assignee: BioFortis, Inc. (IQVIA Holdings, Inc.)
• Inventors: Brocato, Mark, Wang, Jian, Chen, Steven Hsing-Yu
• Primary Examiner(s): Arjomandi, Noosha
• Application Number:
  US13/732,347
• Publication Number:
  US 20130151572A1
• Time in Patent Office: 1,758 Days
• Field of Search: 707705
• CPC Class Codes: G06F 16/213 with details for schema evolution support
• CPC Class Codes: G06F 16/2425 Iterative querying; Query formulation based on the results of a preceding query
• CPC Class Codes: G06F 16/2428 Query predicate definition using graphical user interfaces, including menus and forms G06F16/2423 takes precedence

Abstract

A schema parser may determine one or more datasets of a database schema, wherein the datasets include one or more fields from a data source and represents data corresponding to the one or more fields. An input handler may receive a selection of one or more of the datasets via an interface. A translation engine may provide operations for refining the data of the selected datasets into a result set via a query, wherein the operations may be determined based on metadata defining relationships amongst the data sources and fields. A query engine may provide a graphical query including operational flow indicators indicating a directional flow of the query from the selected datasets with the selected operation to the result set.

Claims

1. A system comprising:

one or more processors;

a database schema including a plurality of data sources, each data source including one or more fields for storing data, and metadata defining relationships amongst the fields within or between data sources;

a schema parser executed by at least one of the processors and configured to determine one or more datasets of data stored within or referenced from the database schema, wherein a dataset includes one or more fields from the database schema and represents the data stored in the one or more fields;

an input handler executed by at least one of the processors and configured to receive a user'"'"'s selection of one or more of the datasets via a graphical user interface, wherein the input handler is configured to determine that a first graphical icon representing a first dataset is graphically associated within the graphical user interface with a second graphical icon representing a second dataset;

a translation engine executed by at least one of the processors and configured to provide operations for refining the data of the selected datasets into a result set via a query, wherein the translation engine is configured to determine natural language queries to provide based on the relationships identified by the metadata, the natural language queries including intuitive descriptions of the operations based on the relationships identified by the metadata and an experience level of the user, the intuitive descriptions being different for users with different experience levels, wherein the translation engine is configured to provide, responsive to the graphical association of the first and second icons, natural language queries to perform between the first dataset and the second dataset, wherein the natural language queries are determined based on the relationships of the datasets as stored or derived from the metadata, wherein the input handler is configured to receive a selection of one of the natural language queries provided by the translation engine; and

a query engine executed by at least one of the processors and configured to provide a graphical depiction of the query via the interface, the graphical query including operational flow indicators indicating a directional flow of the query from the selected datasets with the selected natural language query resulting in the result set.

2. The system of claim 1 wherein the schema parser is configured to determine the datasets based on one or more keys from each data source, wherein the metadata describes the relationship amongst the keys of the data sources.

3. The system of claim 1, wherein the natural language query includes an alias for the selected datasets as provided by the user.

4. The system of claim 1 wherein:

graphically associating the first icon with the second icon includes dragging the first icon and dropping the first icon onto the second icon.

5. The system of claim 4, wherein, in response to the input handler receiving a selection of one of the provided natural language queries, the query engine is configured to provide a graphical depiction of the query via the interface, the graphical query including a third icon representing a third dataset formed in response to the selected natural language queries, the third icon being connected to the first and second icons by one or more operational flow indicators indicating a directional flow of the query from the first and second datasets to the third dataset.

6. The system of claim 1 wherein the input handler is configured to receive a selection of a first graphical icon representing a first dataset and the query engine is configured to provide the first graphical icon representing the first dataset in the graphical query.

7. The system of claim 1 wherein the input handler is configured to receive an alias to at least one of the selected datasets in the graphical query, wherein the alias includes a user-provided name for the selected datasets.

8. The system of claim 1 further comprising a logic engine configured to assemble a machine readable structured query based on the graphical query.

9. The system of claim 8 wherein the machine readable structured query includes a structured query language (SQL) query.

10. The system of claim 8 wherein the logic engine is configured to process elements of the graphical query, beginning with the result set and proceeding to the data sources, to assemble the structured query.

11. The system of claim 8 wherein the logic engine is configured to execute the structured query against the database and return only results to which the user is allowed access based on an access control list (ACL).

12. The system of claim 9 wherein the logic engine is configured to:

determine a local identifier corresponding to a selected dataset from the graphical query;

determine one or more fields of the selected dataset associated with the operation for refining the data of the selected dataset;

determine the natural language query corresponding to the one or more fields of the selected dataset; and

provide the local identifier, the one or more fields of the selected dataset, and the operation in the structured query language (SQL) query.

13. The system of claim 9 wherein:

the logic engine comprises a plurality of different subroutines, each different subroutine being configured to process a different type of operation represented by a particular type of element in the graphical query to generate a SQL substatement of the element'"'"'s operation;

the logic engine is further configured to process elements in the graphical query, beginning with the result set and proceeding to the data sources, to identify columns of the data sources referenced by the SQL substatements and to add those columns to a SQL SELECT statement produced by the subroutine that processes data source elements; and

the logic engine is further configured to incorporate the SQL substatements into a complete machine readable SQL query.

14. The system of claim 1 wherein the database schema includes a plurality of database objects of a database.

15. The system of claim 14 wherein the database objects include tables having one or more columns for storing the data.

16. The system of claim 14 wherein the database objects include database views having one or more columns representing the data.

17. The system of claim 1, wherein the system is configured to generate additional metadata based on user interaction with the input handler.

18. A computer-implemented method of constructing a query with which to retrieve information from a database, the method comprising:

receiving one or more keywords input from a user;

determining, by at least one processor of a computer system, a first dataset identified in a schema of the database based on the received one or more keywords and metadata associated with the first dataset;

determining, by at least one processor of the computer system, a second dataset identified in the schema of the database based on input from the user and metadata associated with the second dataset;

representing graphically, by a display of the computer system, the determined first dataset as a first icon and the determined second dataset as a second icon in a canvas presented to the user;

receiving information that the user has graphically associated the first icon with the second icon on the canvas;

in response to the user'"'"'s graphical association of the first and second icons, generating a combination dataset of the first and second datasets;

representing graphically the combination dataset as a third icon in the canvas and representing graphically in the canvas a relationship between the combination dataset and the first and second datasets;

presenting a natural language query to the user, the natural language query including an intuitive description of a query based on the relationship between the combination dataset and the first and second datasets and an experience level of the user, the intuitive description being different for users with different experience levels;

receiving a selection of the natural language query from the user;

constructing, by at least one processor of the computer system in response to receiving the selection of the natural language query from the user, a machine-readable structured query based on the first dataset, the second dataset, the combination dataset and the relationship between the first dataset, the second dataset, and the combination dataset; and

returning data from the database, the returned data corresponding to an execution of the machine-readable structured query against the database.

19. The method of claim 18, wherein the one or more keywords correspond to a data source, metadata of the first dataset, a field of the first dataset, or data stored in a field of the first dataset.

20. The method of claim 19, wherein the determination of the first dataset is based on a comparison of the one or more input keywords and metadata associated with a data source, metadata of the first dataset, a field of the first dataset, or data stored in a field of the first dataset.

21. The method of claim 18, wherein determining a first dataset comprises:

presenting to the user a plurality of potential first datasets identified in a schema of the database based on the input keywords, wherein the identified first datasets include data source metadata, field metadata, data value metadata, or data values that correspond to the one or more keywords; and

receiving a selection by the user of the first dataset from the plurality of potential first datasets.

22. The method of claim 18, wherein the natural language query includes verbs and nouns based on the relationship between the combination dataset and the first and second datasets and metadata in the schema defining the relationship between the combination dataset and the first and second datasets.

23. The method of claim 18, wherein the graphical association of the first graphical icon and the second graphical icon includes dragging and dropping the first graphical icon onto the second graphical icon within the display.

24. The method of claim 18 wherein constructing the structured query comprises constructing the structured query based on a depth-first analysis of the graphical association of the first and second icons.

25. A method of constructing a query with which to retrieve information from a database, the method comprising:

representing graphically a first dataset of a database as a first icon and a second dataset of the database as a second icon in a canvas presented to a user on a display of a computer system;

receiving an indication to combine the first dataset with the second dataset, wherein the indication is received in response to the first icon being graphically associated with the second icon in the canvas;

based on the received indication and metadata associated with the first dataset and the second dataset, presenting to the user on the display of the computer system natural language query options for combining elements of the first and second datasets, the natural language query options including intuitive descriptions of the combining elements based on the metadata and an experience level of the user, the intuitive descriptions being different for users with different experience levels;

in response to the user'"'"'s selection of one of the presented natural language query options, generating a third icon in the canvas representing a combination dataset of elements of the first and second datasets;

representing user-defined relationships between the first and second datasets and the combination dataset as a connected graph of the first, second and third icons, wherein the connected graph presents a graphical representation of the query to the user;

constructing, by at least one processor of the computer system, a machine-readable structured query based on the connected graph; and

returning data from the database, the returned data corresponding to an execution of the machine-readable structured query against the database.

26. The method of claim 25, wherein receiving the indication comprises receiving a selection of the second icon in the canvas.

27. The method of claim 25, wherein receiving the indication comprises:

receiving a selection of the first icon; and

providing, responsive to the selection, one or more related datasets that share a relationship with the first dataset, the one or more related datasets including the second dataset.

28. The method of claim 25, wherein the natural language query options are based on the metadata and the structure of the machine-readable structured query.

29. The method of claim 25, wherein the graphical representation of at least one of the datasets is based on:

receiving one or more keywords input from a user; and

determining the dataset in a schema of the database based on the one or more keywords.

30. The method of claim 25, wherein the user'"'"'s selection of one of the presented natural language query options includes a selection to filter the second dataset through the first dataset to create the combination dataset, which includes only records from the first dataset having a corresponding record in the second dataset.

31. The method of claim 25, wherein the user'"'"'s selection of one of the presented natural language query options includes a selection to combine columns of the first and second datasets to create the combination dataset, which includes columns found in the first and second datasets that are chosen based on criteria specified by the user, wherein the method further comprises receiving the specified criteria from the user.

32. The method of claim 25, wherein the user'"'"'s selection of one of the presented natural language query options includes a selection to create the combination dataset as a union of the first and second datasets, which includes all records from the first and second datasets.

33. The method of claim 25, wherein the user'"'"'s selection of one of the presented natural language query options includes a selection to create the combination dataset as an intersection of the first and second datasets, which includes only records that are in both the first and second datasets.

34. The method of claim 25, wherein the user'"'"'s selection of one of the presented natural language query options includes a selection to create the combination dataset as an exclusion of the first and second datasets, which includes all records that are in the first dataset but not in the second dataset.

35. A system comprising:

one or more processors;

an input handler executed by at least one of the processors and configured to receive a keyword by which to search a content index of a database for a corresponding data source from a plurality of data sources associated with the database, the data sources including metadata, fields and data populating the database;

a search engine executed by at least one of the processors and configured to search the content index for the keyword, and to provide metadata from the content index corresponding to the keyword;

the input handler being configured to receive a selection from the metadata;

a query engine executed by at least one of the processors and configured to provide, responsive to the selection of the metadata, a first graphical icon in a graphical user interface, the first graphical icon representing the selected metadata, and to provide in the graphical user interface a second graphical icon representing a corresponding data source,

wherein the input handler is configured to determine that the first graphical icon is graphically associated within the graphical user interface with the second graphical icon; and

a translation engine configured to provide, responsive to the graphical association of the first and second graphical icons, a list of natural language queries to perform between the selected metadata and the data source, the natural language queries including intuitive descriptions of the natural language queries based on the selected metadata and an experience level of the user, the intuitive descriptions being different for users with different levels of experience,

wherein the query engine is configured to query the database using query parameters based on the data source and a natural language query selected from the list of natural language queries.

36. The system of claim 35, further comprising a schema parser configured to identify the data source corresponding to the keyword based on the selection, wherein:

the schema parser identifies the data source.

37. The system of claim 35 wherein the search engine is configured to provide a list of data sources based on level of relevance between each data source and the keyword.

38. The system of claim 35 wherein determining that the first graphical icon is graphically associated within the graphical user interface with the second graphical icon includes determining that the first graphical icon has been dragged and dropped on the second graphical icon within the graphical user interface.

39. The system of claim 35 wherein the search engine is configured to assemble the content index from the database, the content index including the data sources, fields and data of the database.

40. The system of claim 35 wherein the search engine is configured to return, from the database, data corresponding to the keyword and a structure of the database where data is stored, the structure including the data source and field.

41. A computer-implemented method comprising:

determining, by at least one processor of a computer system, based on metadata associated with data of a database, a plurality of natural language expressions (NLEs) describing operations that may be performed on one or more datasets associated with a graphical query that is displayed to a user through a graphical user interface on a display of the computer system, the plurality of NLEs including intuitive descriptions of the operations based on the metadata and an experience level of the user, the intuitive descriptions being different for users with different levels of experience;

determining, from the graphical query, one or more aliases corresponding to one or more of the datasets, wherein the one or more aliases include a user-provided phrase by which to refer to the corresponding one or more datasets;

providing the plurality of NLEs that describe the operations that may be performed on the one or more datasets, including the one or more aliases corresponding to the one or more datasets presented to the user via the graphical user interface;

receiving a selection by the user of one of the provided plurality of NLEs; and

rendering, in the graphical query, a graphical depiction of the selected NLE on the one or more datasets.

42. The method of claim 41 wherein the rendering comprises rendering, in the graphical query, a result set appearing as a result of performing the selected NLE on the one or more datasets.

43. The method of claim 41 wherein determining which of a plurality of operations may be performed comprises determining the operations based on a relationship between keys associated with data sources of the database corresponding to the datasets.

44. A computer-implemented method comprising:

providing a graphical user interface displayed to a user on a display of a computer system, the interface being configured to allow the user to generate a graphical representation of a structured query for data of a database;

receiving, via the graphical user interface, selections of dataset icons corresponding to respective datasets of the database, indications of graphical associations between two or more dataset icons, and operations to perform on the datasets, wherein at least one of the operations is a natural language query that is selected from a plurality of operations that are provided based on metadata associated with the respective datasets of the database and an indication of a graphical association between the two or more dataset icons, the natural language query including an intuitive description of at least one operation based on the metadata and an experience level of the user, the intuitive description being different for users with different levels of experience;

generating, by at least one processor of the computer system, the graphical representation of the structured query in the graphical user interface based on the selections of the dataset icons and the operations to perform on the datasets, the graphical representation including the dataset icon and/or a representation of a selected operation;

generating, by at least one processor of the computer system, the structured query based on the graphical representation;

executing the structured query against the database; and

providing results of the execution of the structured query.

45. The method of claim 44 wherein the receiving comprises determining, from amongst the selections, a target set of data from the database to be returned from the execution.

46. The method of claim 44 wherein generating the graphical representation comprises generating a directional flow indicator for each selected operation, indicating an operation to be performed on one or more of the selected dataset icons.

47. The method of claim 46 wherein generating the structured query comprises generating the structured query based on the directional flow indicators.

48. The method of claim 44 wherein generating the graphical representation comprises receiving a new placement of a selected dataset icon within the graphical representation, wherein the new placement does not change the generated structured query.