Abstract: An inventory, disposition, and order management system and method utilizes multiple data sources to obtain complementary and augmented product data to determine an enhanced set of product data that reflects product inventory and disposition history information in a supply chain. The system and method can utilize the complementary and augmented product data to formulate recommended orders to achieve product dealer sales goals. The system and method compare the product data obtained from the data sources and reconcile any discrepancies. In at least one embodiment, the product data includes product identification data, product inventory data, product configuration data, and product disposition history data. Obtaining data from multiple sources allows the system and method to develop more accurate and complete data through an audit and reconciliation process as opposed to data obtained from a single source.

Abstract: 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.

Abstract: Various embodiments relate generally to data science and data analysis, and computer software and systems, 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 user interfaces may be implemented as computerized tools for presenting summarization of dataset attributes to facilitate discovery, formation, and analysis of interrelated collaborative datasets. In some examples, a method may include receiving data resulting from insight calculations. Insight calculations may be based on a derived dataset attribute. Also, the method may include presenting a data arrangement overview summarizing the data attributes as an aggregation of data attributes in a portion of the user interface.

Abstract: The variable domain data access control system and method described herein use the same variable domain to describe a data security model and a variable domain data model, such as a product configuration model. A variable domain is a set of resource data that can be described using a logical relationship data structure. The variable domain utilizes logical relationship expressions, such as a Boolean logic language, to define resource data in terms of parts, rules and/or attributes, and any other property that can be accessed for viewing, manipulation, or other purposes. The data security model represents an access control list (ACL) that includes security attributes as resource data and uses the same data structure and logical relationship expressions as an associated variable domain data model. An application, such as a configuration engine, can be used to create controlled access to the variable domain data model using the data security model.

Abstract: 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 one or more computerized tools may be configured to discover, form, and analyze, for example, via one or more user interface applications, interrelations among a system of networked collaborative datasets In some examples, a method may include causing transformation of a set of data to an atomized format to form an atomized dataset, monitoring creation of a dataset, and presenting data representing a status of a portion of the creation of the dataset. The status may depict an atomized dataset linked to at least one other dataset.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Various embodiments relate generally to data science and data analysis, and computer software and systems, 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 one or more interfaces, such as user interfaces, may be implemented as computerized tools for presenting summarization of dataset attributes to facilitate discovery, formation, and analysis of interrelated collaborative datasets. In some examples, a method may include presenting data representing summary characteristic data in a user interface. This may include user interface elements each specifying a value of a dataset attribute for a collaborative dataset. Also, the method may include presenting aggregated data attributes for a subset of the collaborative dataset associated with the linked atomized datasets.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Systems and methods to facilitate the collection and processing of content generated by users are disclosed. Specifically, in one embodiment, user generated content may be aggregated from multiple retailers. This user generated content may be processed to obtain a variety of statistical data associated with the user generated content, including an importance metric. This importance metric may be utilized to rank the products of the manufacturer such that statistical, or other, data related to the manufacturer's products may be presented to a user in the order of product importance.

Abstract: The variable domain data access control system and method described herein use the same variable domain to describe a data security model and a variable domain data model, such as a product configuration model. A variable domain is a set of resource data that can be described using a logical relationship data structure. The variable domain utilizes logical relationship expressions, such as a Boolean logic language, to define resource data in terms of parts, rules and/or attributes, and any other property that can be accessed for viewing, manipulation, or other purposes. The data security model represents an access control list (ACL) that includes security attributes as resource data and uses the same data structure and logical relationship expressions as an associated variable domain data model. An application, such as a configuration engine, can be used to create controlled access to the variable domain data model using the data security model.

Abstract: The variable domain data access control system and method described herein use the same variable domain to describe a data security model and a variable domain data model, such as a product configuration model. A variable domain is a set of resource data that can be described using a logical relationship data structure. The variable domain utilizes logical relationship expressions, such as a Boolean logic language, to define resource data in terms of parts, rules and/or attributes, and any other property that can be accessed for viewing, manipulation, or other purposes. The data security model represents an access control list (ACL) that includes security attributes as resource data and uses the same data structure and logical relationship expressions as an associated variable domain data model. An application, such as a configuration engine, can be used to create controlled access to the variable domain data model using the data security model.

Abstract: The variable domain data access control system and method described herein use the same variable domain to describe a data security model and a variable domain data model, such as a product configuration model. A variable domain is a set of resource data that can be described using a logical relationship data structure. The variable domain utilizes logical relationship expressions, such as a Boolean logic language, to define resource data in terms of parts, rules and/or attributes, and any other property that can be accessed for viewing, manipulation, or other purposes. The data security model represents an access control list (ACL) that includes security attributes as resource data and uses the same data structure and logical relationship expressions as an associated variable domain data model. An application, such as a configuration engine, can be used to create controlled access to the variable domain data model using the data security model.

Abstract: Systems and methods to facilitate the collection and processing of content generated by users are disclosed. Specifically, in one embodiment, user generated content may be aggregated from multiple retailers. This user generated content may be processed to obtain a variety of statistical data associated with the user generated content, including an importance metric. This importance metric may be utilized to rank the products of the manufacturer such that statistical, or other, data related to the manufacturer's products may be presented to a user in the order of product importance.

Abstract: A system and method for presenting information organized by hierarchy levels displays navigation bars related to the hierarchy of nodes from the root node to the one or more sub-nodes having the lowest hierarchy level and hides unrelated sub-nodes, such as siblings of ancestors of the lowest hierarchy level node. The relevant levels of the hierarchy are displayed as a stacked box metaphor to provide strong state information for information associated with a desired sub-node of the lowest selected hierarchy level. Index tabs provide a view of heterogeneous sections sliced across a desired attribute to provide rapid navigation through a hierarchy of non-homogeneous classifiers to find information having an indexed attribute. Activation of a sub-node navigation bar displays information associated with the sub-node or displays child nodes and hides sibling nodes of the activated sub-node. An activation icon associated with navigation bars allows a user to browse upwards in the hierarchy level as desired.