Predictive determination of constraint data for application with linked data in graph-based datasets associated with a data-driven collaborative dataset platform
Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to interface among repositories of disparate datasets and computing machine-based entities configured to access datasets, and, more specifically, to a computing and data storage platform to implement predict data constraints to validate one or more portions of a dataset, according to at least some examples. For example, a method may include predicting a subset of constraint data to validate a graph-based data arrangement, and analyzing the graph-based data arrangement against a subset of constraint data to determine an action. At least one action may include validating data in a graph-based data arrangement. Also, the method may include integrating graph-based data arrangement into a graph data arrangement responsive to determining data representing a validation.
1. A method comprising:
receiving subsets of data as columnar data associated with a data arrangement into a collaborative dataset consolidation system at ingestion, the data arrangement being a tabular data arrangement including each of the subsets of data as a column;
detecting classification data and joinable data;
forming a graph-based data arrangement from a subset of data in a column based on a portion of the ingested data;
identifying an ontological reference associated with the graph-based data arrangement;
predicting a subset of constraint data includes identifying the subset of constraint data as a function of contextual information to validate the graph-based data arrangement;
analyzing the graph-based data arrangement against the subset of constraint data to determine an action, at least one action includes validating data in the graph-based data arrangement and applying the aggregated constraint data to validate the ingested data, validating the ingested data, and integrating the ingested data as graph data into the graph data arrangement responsive to the aggregated constraint data, identifying a plurality of user accounts associated with the subsets of constraint data, and generating electronic notifications to each of the user accounts including data specifying implementation of a corresponding one of the subsets of constraint data;
integrating graph-based data arrangement into a graph data arrangement responsive to determining data representing a validation;
identifying classification types associated with a plurality of columns of the ingested data, which includes classification data and joinable data;
determining subsets of constraint data associated with the classification types associated with different portions of the graph data arrangement; and
aggregating the subsets of constraint data to form aggregated constraint data.
2. The method of claim 1 wherein identifying classification types comprises:
calculating a degree of joinability.
3. The method of claim 1 wherein the subset of constraint data includes data representing a shape graph.
4. The method of claim 1 further comprising:
analyzing the graph-based data arrangement to determine equivalent portions of the graph data arrangement.
5. The method of claim 4 further comprising:
identifying a classification type associated with the graph-based data arrangement;
correlating a first subset of data representing the classification type for the graph-based data arrangement to a second subset of data presenting a classification type for a portion of the graph data arrangement; and
matching the first subset of data and the second subset of data.
6. The method of claim 1 wherein determining the subsets of constraint data comprises:
identifying the subsets of data in the graph data arrangement at least two of which are disposed in separate data repositories.
7. The method of claim 1 wherein aggregating the subsets of constraint data to form the aggregated constraint data comprises:
generating reshaped graph data.
8. The method of claim 1 further comprising:
invalidating the ingested data; and
generating a corrective action as the action.
9. The method of claim 8 further comprising:
identifying at least one subset of the subsets of constraint data associated with invalidating the ingested data to form an invalidated subset of constraint data;
identifying a user account associated with the invalidated subset of constraint data; and
generating an electronic notification in association with the user account to include data specifying implementation of a corresponding the invalidated subset of constraint data.
10. The method of claim 1 wherein identifying the subset of constraint data comprises:
accessing a layer file including the subset of constraint data.
11. An apparatus comprising:
a memory including executable instructions; and
a processor, responsive to executing the instructions, is configured to:
receive subsets of data as columnar data associated with a data arrangement into a collaborative dataset consolidation system at ingestion, the data arrangement being a tabular data arrangement including each of the subsets of data as a column;
detect classification data and joinable data;
form a graph-based data arrangement from a subset of data in a column based on a portion of the ingested data;
identify an ontological reference associated with the graph-based data arrangement;
predict a subset of constraint data including identifying the subset of constraint data as a function of contextual information to validate the graph-based data arrangement;
analyze the graph-based data arrangement against the subset of constraint data to determine an action, at least one action includes validating data in the graph-based data arrangement and applying the aggregated constraint data to validate the ingested data, validating the ingested data, and integrating the ingested data as graph data into the graph data arrangement responsive to the aggregated constraint data, identifying a plurality of user accounts associated with the subsets of constraint data, and generating electronic notifications to each of the user accounts including data specifying implementation of a corresponding one of the subsets of constraint data;
integrate graph-based data arrangement into a graph data arrangement responsive to determining data representing a validation;
identifying classification types associated with a plurality of columns of the ingested data, which includes classification data and joinable data;
determine subsets of constraint data associated with subsets of data in the graph data arrangement;
extract the subsets of constraint data associated with classification types associated with different portions of the graph data arrangement; and
aggregate the subsets of constraint data to form aggregated constraint data.
12. The apparatus of claim 11 wherein the processor is further configured to:
identify the subset of constraint data as a shape graph to validate the graph-based data arrangement as a function of context.
13. The apparatus of claim 11 wherein the processor is further configured to:
analyze the graph-based data arrangement to determine equivalent portions of the graph data arrangement; and
identify one or more classification types associated with the graph-based data arrangement.
14. The apparatus of claim 11 wherein a subset of the instructions to cause the processor to aggregate the subsets of constraint data to form the aggregated constraint data comprises further instructions to cause the processor to:
generate reshaped graph data.
15. A non-transitory computer readable medium having one or more computer program instructions configured to perform a computerized method, the computerized method comprising:
receiving subsets of data as columnar data associated with a data arrangement into a collaborative dataset consolidation system at ingestion, the data arrangement being a tabular data arrangement including each of the subsets of data as a column;
detecting classification data and joinable data;
forming a graph-based data arrangement from a subset of data in a column based on a portion of the ingested data;
identifying an ontological reference associated with the graph-based data arrangement;
predicting a subset of constraint data includes identifying the subset of constraint data as a function of contextual information to validate the graph-based data arrangement;
analyzing the graph-based data arrangement against the subset of constraint data to determine an action, at least one action includes validating data in the graph-based data arrangement and applying the aggregated constraint data to validate the ingested data, validating the ingested data, and integrating the ingested data as graph data into the graph data arrangement responsive to the aggregated constraint data, identifying a plurality of user accounts associated with the subsets of constraint data, and generating electronic notifications to each of the user accounts including data specifying implementation of a corresponding one of the subsets of constraint data;
integrating graph-based data arrangement into a graph data arrangement responsive to determining data representing a validation;
identifying classification types associated with a plurality of columns of the ingested data, which includes classification data and joinable data;
determining subsets of constraint data associated with the classification types associated with different portions of the graph data arrangement; and
aggregating the subsets of constraint data to form aggregated constraint data.
16. The computerized method of claim 15 wherein identifying classification types comprises:
calculating a degree of joinability.
17. The computerized method of claim 15 wherein the subset of constraint data includes data representing a shape graph.
18. The computerized method of claim 15 further comprising:
analyzing the graph-based data arrangement to determine equivalent portions of the graph data arrangement.
19. The computerized method of claim 15 further comprising:
identifying a classification type associated with the graph-based data arrangement.