Generating and analyzing a data model to identify relevant data catalog data derived from graph-based data arrangements to perform an action
Various embodiments relate generally to data science and data analysis, computer software and systems, and data-driven control systems and algorithms based on graph-based data arrangements, and, more specifically, to a computing platform configured to receive and analyze datasets to implement a data model with which to identify relevant data catalog data derived from graph-based data arrangements, whereby a processor may be configured to cause implementation of subsets of programmatic executable instructions based on relevant data catalog data, at least one example of which generates a concept interface portion adapted to an associated concept, among other things. In some examples, a method may include identifying attributes associated with data values linked to a conceptual entity, determining criteria data of a targeted application, selecting programmatic executable instructions based on the criteria data, and extracting data from a graph data arrangement as a function of the attributes, among other things.
1. A computer-implemented method comprising:
receiving data representing a conceptual entity linked to a dataset stored in association with a graph data arrangement that derives the dataset from multiple data sources communicatively coupled to a computing system that includes one or more processors and memory;
identifying data representing a subset of attributes associated with data values linked to the data representing the conceptual entity;
identifying criteria data of a targeted application;
selecting subsets of programmatic executable instructions to consume data associated with the subset of attributes based on the criteria data of the targeted application;
extracting data from the graph data arrangement as a function of the subset of attributes to form extracted data; and
causing implementation of the subsets of the programmatic executable instructions to generate a concept interface portion of a concept card to be displayed, a size of the concept interface portion being determined based on a degree of relevancy of metadata associated with each concept interface portion of the concept card.
2. The computer-implemented method of claim 1 wherein causing implementation of the subsets of the programmatic executable instructions comprises:
activating a subset of application programming interfaces (“APIs”) configured to access the data from the graph data arrangement.
3. The computer-implemented method of claim 2 further comprising:
receiving the extracted data into an application configured to access a data catalog; and
receiving user input data to modify the graph data arrangement based on the extracted data.
4. The computer-implemented method of claim 1 wherein identifying the data representing the subset of attributes comprises:
identifying metadata associated with at least one metadata profile data file.
5. The computer-implemented method of claim 1 wherein identifying the data representing the subset of attributes with data values comprises:
identifying the data values as classified data values.
6. The computer-implemented method of claim 1 further comprising:
linking data representing the subset of attributes associated with the data values linked to the data representing the conceptual entity as a function of a degree of correlation.
7. The computer-implemented method of claim 1 further comprising:
accessing data representing user interface dimensions; and
modifying implementation of the subsets of the programmatic executable instructions based on the user interface dimensions.
8. The computer-implemented method of claim 1 further comprising:
displaying data associated with the data representing the subset of attributes in a concept interface portion.
9. The computer-implemented method of claim 1 further comprising:
displaying data associated with the data representing the subset of attributes in a concept interface portion that includes a descriptive interface portion, a relevant user account interface portion, a relevant resource interface portion, and a predicted action interface portion.
10. The computer-implemented method of claim 1 wherein the targeted application is a user interface generation application.
11. The computer-implemented method of claim 1 wherein causing implementation of the subsets of the programmatic executable instructions comprises:
executing instructions to cause display of a concept interface portion in a user interface.
12. The computer-implemented method of claim 1 wherein receiving the data representing the conceptual entity comprises:
receiving the data as a user input via a search field in a user interface.
13. The computer-implemented method of claim 1 wherein receiving the data representing the conceptual entity comprises:
accessing data representing at least a portion of the graph data arrangement;
implementing a natural language processing (“NLP”) algorithm to identify a concept; and
classifying the concept as the data representing the conceptual entity to form a classified concept.
14. The computer-implemented method of claim 1 further comprising:
accessing ancillary data associated with the conceptual entity from the graph data arrangement;
classifying the subset of attributes; and
generating classification values as the data values.
15. The computer-implemented method of claim 14 further comprising:
classifying the subset of attributes as one or more of descriptive data, relevant user account data, relevant resource data, and predicted action data.
16. The computer-implemented method of claim 14 further comprising:
clustering data to classify the subset of attributes.
17. The computer-implemented method of claim 1 further comprising:
monitoring multiple user inputs representing conceptual entity data;
training logic configured to implement a data classifier; and
forming a data model with which to classify the subsets of attributes to select the subsets of programmatic executable instructions.
18. A system comprising:
a data store configured to receive streams of data via a network into an application computing platform; and
a processor configured to execute instructions to implement an application configured to:
receive data representing a conceptual entity linked to a dataset stored in association with a graph data arrangement that derives the dataset from multiple data sources communicatively coupled to a computing system that includes one or more processors and memory;
identify data representing a subset of attributes associated with data values linked to the data representing the conceptual entity;
determine criteria data of a targeted application;
select subsets of programmatic executable instructions to consume data associated with the subset of attributes based on the criteria data of the targeted application;
extract data from the graph data arrangement as a function of the subset of attributes to form extracted data; and
cause implementation of the subsets of the programmatic executable instructions to generate a concept interface portion of a concept card to be displayed, a size of the concept interface portion being determined based on a degree of relevancy of metadata associated with each concept interface portion of the concept card.
19. The system of claim 18 wherein the processor is further configured to:
activate a subset of application programming interfaces (“APIs”) configured to access the data from the graph data arrangement.
20. The system of claim 18 wherein the processor is further configured to:
receive the extracted data into an application configured to access a data catalog; and
receive user input data to modify the graph data arrangement based on the extracted data.