AUTOMATED DATA QUALITY DETECTION FOR UNSTRUCTURED DATA

    公开(公告)号:US20240419641A1

    公开(公告)日:2024-12-19

    申请号:US18209273

    申请日:2023-06-13

    Abstract: This disclosure relates to assessment of data quality for unstructured data. In some aspects, a method includes obtaining, by one or more computing devices, metadata of multiple data files; analyzing a graph database representative of the multiple data files and generated using the metadata, to identify unstructured data included in one or more data files, the graph database representing features of the multiple data files, and relationships among the features of the multiple data files; obtaining a set of customized rules for the unstructured data based on context of the unstructured data; determining that the unstructured data fails to satisfy the set of customized rules; and in response to determining that the unstructured data fails to satisfy the set of customized rules, modifying the unstructured data to satisfy the set of customized rules.

    REPRESENTING AND USING METADATA VIA THE USE OF GRAPH DATABASE

    公开(公告)号:US20240296145A1

    公开(公告)日:2024-09-05

    申请号:US18117169

    申请日:2023-03-03

    CPC classification number: G06F16/156 G06F16/9024

    Abstract: This disclosure relates to representing and using metadata via graph database. In some aspects, a method includes receiving, at one or more computing devices, first metadata associated with data files from one or more data sources, the first metadata representing a plurality of features of associated data included in the data files, the plurality of features including at least one of a file name, a table name, an attribute, a row name, and a column name; determining relationships among the plurality of features to generate second metadata representing content of the data files; and generating a graph database representing the content of the data files, the graph database including a set of nodes and a set of edges, wherein each node in the set of nodes represents a feature of the plurality of features, and each edge represents a relationship between two nodes in the set of nodes.

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