Bank of America Corporation

Brad Romano

Shashi Thanikella

Joseph Benjamin Castinado

Patrick Nicholas Lawrence

Suki Ramasamy

Jisoo Lee

William August Stahlhut

John Christopher Checco

Lekha Ananthakrishnan

John Abraham

John R Sampson

Jason E Martens

Sachin M Nerurkar

Shashi Tanikella

Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Automated event processing computing platform for handling and enriching blockchain data

A data structure management system includes a first database, a second database, and a processing engine. The first database includes a first file with a first term and a corresponding first metadata, and a second file with the first term and a corresponding second metadata. The processing engine extracts the first file and the second file from the first database in a first format. It links the first term with the first metadata from the first file and the second metadata from the second file. It transforms the extracted first file and second file from the first format into a second format while maintaining the link between the first term, the first metadata, and the second metadata. It then exports the transformed first file and second file to a second database in the second format with the link between the first term, the first metadata, and the second metadata intact.

System and method for data structure migration control

A parallel processing device includes a parallel processing engine implemented by a processor. The parallel processing engine is configured to execute a shell script for each particular processing job in a queue of processing jobs to run. The shell script is configured to dynamically generate a configuration file for each particular processing job. The configuration file instructs a network of computing systems to run the particular processing job using a particular number of parallel partitions corresponding to a parallel partitions parameter associated with the particular job. The configuration file includes randomized scratch directories for computing nodes within the network of computing systems and a calculated container size for the particular processing job. Each processing job is run on the network of computing systems according to the dynamically-generated configuration file of the particular processing job.

Conserving computing resources during network parallel processing

A system for communication between two or more computer programs is disclosed. The system includes a memory, an interface, and a processor. The memory stores a first file, expected metadata for the first file, and expected metadata for one or more fields in the first file. The interface receives a file from a computer program. The file comprises fields that each comprise information provided by one or more sources. The processor executes a second computer program which extracts a first set of file metadata from the received file, compares the extracted first set of file metadata to the expected metadata, and determines if the extracted first set of file metadata corresponds to the expected metadata. If the extracted first set of file metadata corresponds to the expected metadata for the first file, then the processor performs analogous comparisons at a field level and stores the first file in the memory.

System and method for inter-program file control communication

An adaptive machine learning system for predicting file controls includes a memory, an interface, and a processor. The memory stores a plurality of controls for incoming files and the interface receives a first file and a second file. The first file has a first property and the second file has a second property. The processor determines a type for each of the first property and the second property, wherein the type of each property is related to a first file control. The processor also determines that the first property and the second property each satisfy the first file control. If the value of the first property and the second property are above a first threshold, the processor changes a value of the first control for incoming files.

Machine learning method and system for predicting file controls

A system for file management in data structures is disclosed. The system includes a memory, an extraction engine, an enrichment engine, a portal, and a transmission engine. The memory stores a first database and a memory. The extraction engine extracts columns and fields and associates them with extracted terms. The enrichment engine determines an end-to-end dataflow of the data from extracted metadata and loads the associated data into the memory. Enrichment engine performs either a full load comprising loading all the associated data onto the memory or a delta load comprising comparing the extracted data with data stored in the memory and loading any different data from the extracted data onto the memory. The enrichment engine also generates a journal recording metadata associated with the full or delta load. A portal displays the end-to-end dataflow of the associated data and a transmission engine transmits communication identifying incomplete associated data.

System and method for file management in data structures

Embodiments of the invention are directed to a system, method, and computer program product for leveraging and improving distributed computing cluster architecture by installing a first version and a second version of an information server platform on separate pools of nodes within the same physical distributed computing cluster. The system generates unique file directory storage locations within the cluster allowing for the separate binaries associated with each of the versions to be accurately distinguished from one another by a resource manager tool. The two versions are able to coexist within the same physical storage location inside the distributed computing cluster. Concurrent version installations within the same cluster are advantageous for testing and verifying a newer version before ultimately uninstalling the older version in that a seamless transition between versions is achievable with uninterrupted service. Additionally, the storage structure allows for efficient sharing of data between domains within the cluster itself.

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Furlong, PA, United States of America

Brad Romano