Data.world, Inc.

Coremetrics, Inc.

Brett A Hurt

David Lee Griffith

Bryon Kristen Jacob

Jon Loyens

Triet Minh Le

Arthur Albert Keen

Shad William Reynolds

Joseph Boutros

Alexander John Zelenak

Keith Henning

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a system may include an atomized workflow loader configured to receive an atomized dataset to load into a data store, and to determine resource requirements data to describe at least one resource requirement. The atomized workflow loader may be further configured to select a data store type based on a resource requirement, and perform a load operation of the atomized dataset as a function of the data store type.

Loading collaborative datasets into data stores for queries via distributed computer networks

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a system may include data ingestion controller configured to format datasets to form a first and a second atomized dataset, the second atomized dataset including the first atomized dataset and one or more other atomized datasets. The system may include a dataset query engine configured to identify a portion of a dataset relevant to a query, and to retrieve query results from at least one of different data repositories.

Consolidator platform to implement collaborative datasets via distributed computer networks

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving data representing a query into a collaborative dataset consolidation system, identifying datasets relevant to the query, generating one or more queries to access disparate data repositories, and retrieving data representing query results. In some cases, one or more queries are applied (e.g., as a federated query) to atomized datasets stored in one or more atomized data stores, at least two of which may be different.

Collaborative dataset consolidation via distributed computer networks

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving data representing a query of a consolidated dataset that may include datasets formatted atomized datasets, analyzing the query to classify portions of the query to form classified query portions, partitioning the query into sub-queries as a function of a classification type for each of the classified query portions, and retrieving data representing a query result from distributed data repositories.

Query generation for collaborative datasets

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving a dataset having a data format into a dataset ingestion controller configured to form a collaborative dataset, interpreting data of the dataset against data classifications at an inference engine to derive at least an inferred attribute, associating the data with annotative data identifying the inferred attribute, and converting the dataset at a format converter to form an atomized dataset.

Dataset analysis and dataset attribute inferencing to form collaborative datasets

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving a dataset and dataset attributes and identifying a first version of the dataset. The method may include identifying data that varies from a first version of the dataset, and generating a second version of the dataset to include a first subset and a second subset of atomized data. The method may include storing subsets of atomized data points as an atomized dataset.

Growing community of inventors

Austin, TX, United States of America

Brett A Hurt