Embodiments of the invention can include a system and method for managing a plurality of data feeds to be loaded into a database. The method includes obtaining a script which specifies a query. The method includes executing the query against a source to extract a result set and consulting the script to determine a format for the data feed. The method also includes converting the result set in accordance with the format to create the data feed and transporting the data feed to be loaded into the database.

Systems and methods for managing a highly available distributed hybrid database comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: receive a query from a user device to retrieve data from a distributed database comprising a source node, a first plurality of replica nodes, and a second plurality of replica nodes, wherein the source node and the first plurality of replica nodes form a transactional cluster, and wherein the second plurality of replica nodes forms an analytical cluster; determine whether to process the query using the transactional cluster or the analytical cluster based on one or more rules; translate the query into a first protocol that the determined cluster comprehends; select a replica node corresponding to the determined cluster; process the query using the selected replica node; and send data associated with results from processing the query to the user device.

A tool for standardized layout transformations of BIDI data exchanged between legacy and modern systems is provided. The tool retrieves client connection information from a client request for data. The tool determines, based, at least in part, on the client connection information, a client application's operating system. The tool determines whether the data requested in the client request is BIDI data. Responsive to a determination that the data requested is BIDI data, the tool initiates a layout transformation of the data requested at a single point within the database server. The tool returns transformed BIDI data to the client application.

A system comprises a processor that that receives, through a network, a first data structure from a first source system. Further, the processor receives, through the network, a second data structure from a second source system. In addition, the processor normalizes the first data structure and the second data structure according to a common interface such that at least one constituent of the common interface is immutable, the common interface is backward compatible, and the common interface is forward compatible. The first data structure is at least partially distinct from the second data structure.

A bipartite application implements a table auto-completion (TAC) algorithm on the client side and the server side. A client module runs a local model of the TAC algorithm on a user device and a server module runs a global model of the TAC algorithm on a server machine. The local model is continuously adapted through on-the-fly training, with as few as a negative example, to perform TAC on the client side, one document at a time. Knowledge thus learned by the local model is used to improve the global model on the server side. The global model can be utilized to automatically and intelligently extract table information from a large number of documents with significantly improved accuracy, requiring minimal human intervention even on complex tables.

Systems and methods for mapping data fields between flat files and relational databases are disclosed. For example, an operator of a computing system may wish to export select fields from a relational database to a data file. The operator must then manipulate the data file's field header to conform to a defined specification. A computer program may automatically map the fields in that field header to the field names identified in the specification. The program may then rename the fields in the field header to that of the corresponding, specified field names.

Embodiments of the present disclosure provide for improved mapping from sequential semi-structured data of a first custom data format to a second custom data format. The improved mechanism for mapping between custom data formats significantly reducing the amount of manual effort otherwise used for creating mapping rules. Example embodiments utilize a state extractor model that extracts an untrained modified finite state machine embodied by a skeleton set of extracted states from particular sequential semi-structured input data, and generate a trained modified finite state machine that maps the first custom data format to the second custom data format based at least in part on the untrained modified finite state machine, sequential semi-structured input data of the first custom data format, and database structured output data of the second custom data format. The trained modified finite state machine may be used for subsequent processing data of the first custom data format.

Automatically mapping unlabeled input data onto a target schema via semantic type detection is described. The input data includes data elements that are structured as 2D table rows and columns forming cells. Each data element is included in a cell. The target schema includes a set of fields. Schema mapping includes mapping each column to one or more fields. More particularly, the fields are clustered into field clusters, where each field cluster includes one or more of the fields. Each column is automatically mapped to one of the field clusters of the set of field clusters. The mapping between schema fields and data columns is automatically performed based on appropriate pairings of the detected semantic types, where the semantic types are encoded in vector representations of the fields, the field clusters, and the data elements.

Various methods, apparatuses/systems, and media for automatically extracting information from unstructured data are provided. A receiver receives digitized data of a document having unstructured data format. A processor applies machine learning models for sectioning the digitized data. An OCR device applies an OCR processing to the sectioned digitized data. The processor matches the sectioned digitized data to patterns and rules; applies classification models to the matched digitized data to identify entities and events from the sectioned digitized data; automatically link each entity with corresponding event in a hierarchical format to generate a document having structured data format; and output the document having the structured data with metadata having the linked entity with corresponding event in the hierarchical format to downstream applications.

An integrated management server comprising: a data formatting means for receiving sales record information from a plurality of distributor terminals of a plurality of distributors which are selling products to retailers; a data matching means for updating brand master information for universally managing alcoholic beverage brands sold to the retailers across the plurality of distributors based on each of the received sales record information; and a brand Identification means for analyzing image related information received from a user terminal, identifying an alcoholic beverage brand by comparing a feature information corresponding to an alcoholic beverage brand registered in the brand master information, and sending information related to identified alcoholic beverage brand to the user terminal; and the user terminal comprising: a display means for displaying information on the sent alcoholic beverage brand.