Methods and systems disclosed herein extend an entity's private cloud security model to the entity's public cloud. Public cloud access permissions are defined, in accordance with a security model implemented in the entity's private cloud, for one or more of the entity's public cloud resources. The public cloud permissions are pushed or otherwise provided to an access module within the private cloud. Upon receiving a request to access a public cloud resource, the private cloud access module is invoked to grant or deny the access request in accordance with the public cloud access permissions. Similarly, upon receiving a request to access a private cloud resource, the private cloud access module is invoked to process the access request in accordance with private cloud access permissions, thereby beneficially enabling users to interact with a single access interface regardless of whether the resource reside within the entity's cloud platform.

A system and method is provided for providing searchable customer call indexes. Consistent with disclosed embodiments, a system may receive call information associated with telephone conversations between callers and a vendor, the call information including an audio recording or transcript for each telephone conversation. The system may also identify one or more keywords from the audio recordings or transcripts and index the call information into one or more indexes based on the identified keywords. Finally, the system may determine search results responsive to a search query based on the indexing. In some embodiments, changes to customer service may be identified based on the search results.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for enhanced preparation and integration of data sets. In some implementations, data indicating user input that identifies a first data set that includes streaming data and a second data set that includes non-streaming data is received. The first data set and the second data set are integrated to generate a hybrid data set. The data processing system provides access to the hybrid data set through a (i) non-streaming access channel that provides a periodically-refreshed summary of both the streaming data and the non-streaming data and (ii) a streaming access channel that provides a data stream based on combined data of the first data set and the second data set. One or more application programing interfaces are provided. The one or more application programming interfaces allow at least one client device to access the non-streaming access channel and the streaming access channel.

Techniques for modifying queries in a set of nested queries are disclosed. A graphical user interface displays a query detail region alongside a nested query display region. The graphical user interface includes functionality to provide for modification of queries in the nested set of queries. Based on a selection by a user, a query modification tool promotes a query attribute from a child query to one or more parent queries. Based on another selection by a user associated with one query in the set of nested queries, the system deletes an attribute from each query in the set of nested queries. Responsive to a selection to create multiple conditions for a query rule, the system modifies the functionality of the user interface to enable entry of multiple condition characteristics. Based on a further selection, the system creates the multiple conditions for the query rule.

An approach is provided in which a method, system, and program create a plurality of page clusters in feature space from a plurality of feature vectors corresponding to a plurality of unstructured pages. The method, system, and program product assign one of a plurality of machine learning models to each one of the plurality of page clusters based on a relationship in the feature space between the plurality of page clusters and a plurality of training clusters corresponding to the plurality of machine learning models. The method, system, and program product identify one of the plurality of page clusters that corresponds to a selected one of the plurality of unstructured pages, and transform the selected unstructured page into a structured page using a selected one of the plurality of machine learning models assigned to the identified page cluster.

A tree-based format may be implemented for data stored in a data store. A table may be maintained across one or multiple storage nodes in storage slabs. Storage slabs may be mapped to different nodes of a tree. Each node of the tree may be assigned a different range of distribution scheme values which identify what portions of the table are stored in the storage slab. Storage slabs mapped to child nodes in the tree may be assigned portions of the range of distribution scheme values assigned to a parent. Storage nodes may be added or removed for storing the table. Storage slabs may be moved from one storage node to another in order to accommodate the addition or removal of storage nodes.

The invention provides in some aspects a method, executed on a digital data processing system, of mass generation of customized digital content that includes continuously identifying current external events taken by or with respect to a plurality of respective prospective targets and, upon identification of such an event, generating a set of actions, each identifying a digital content piece and a digital delivery mechanism therefor. Each action is generated, according to the method, based on the current identified events for a particular prospective target and on a database of information about prior events taken by or with respect to him/her. The sets of actions are queued upon generation and continuously retrieved on a first-in-first-out basis. And, upon retrieval, an action for generation of digital content for the respective prospective target is selected for transmittal from the set based on quotas associated with that target and/or the delivery mechanism identified for it per the selected action.

Embodiments of the present disclosure may include a method for credit underwriting, the method including receiving a dataset of user details. Embodiments may also include creating a convolutional neural network (CNN) with the dataset of user details. In some embodiments, the convolutional neural network organizes at least a portion of the dataset of user details into a layered and weighted dataset. Embodiments may also include creating an enriched layered and weighted dataset. Embodiments may also include executing a back-propagation operation to remove at least a portion of the layered and weighted data from the layered and weighted dataset. Embodiments may also include receiving a plurality of enriched layered and weighted datasets.

Methods and systems for analyzing data are described. In one embodiment, a method comprises a processor receiving a data analysis algorithm over a network and executing the data analysis algorithm, the data analysis algorithm analyzing data stored in a database using machine learning to identify a database organizational format, the data analysis algorithm identifying one or more locations for a set of data stored on the database based on identifying the database organizational format, the data analysis algorithm parsing the set of data to identify whether any entries in the database associated with the set of data includes a particular value, and the data analysis algorithm communicating over the network at least a first number of entries in the database that include the particular value and a second number of entries in the database that do not include the particular value.

Proposed is a digital multi-channel platform based on a multi-channel, high-layer data-transfer structure accessible by means of web-client applications running on front-end network-enabled devices providing discrete high-layer data-flow and capturing of structured and unstructured data content transferred from the front-end network-enabled devices over a data transmission network to a digital multi-channel back-end system.