Intuit, Inc.

Sreenivasulu Nallapati

Saikiran Sri Thunuguntla

Vijaykumar Hiremath

Keshav Bhashyam

Vasanth Kumar Jagadeesh

Systems and methods for automated techniques that generate queryable database table ownership attribution information in real-time. In addition to generating ownership attribution information, system and methods provide a novel framework for creating bi-partite graphs and generating insightful graph data.

Automated database ownership attribution

Incoming data requests from the perspective of the data lake, are gathered and analyzed to determine the usage of the data. Using the perspective of the data lake avoids the technical challenge of analyzing data usage by different computation points, which are at different locations, perform hard-to-track different operations, and are often reachable only through complicated access protocols. Another technical challenge of mapping between an object path and a table path is solved by generating object path datasets and table path datasets at different levels of abstractions. A comparison is performed, iteratively, from a lower level of granularity and the granularity is increased in the progressive steps. Matches from iterations are unionized to generate a final matching data. Observability metrics are generated using final matching data and are used to perform downstream operations such as controlling data table access, moving data tables to cold storage, decommissioning unused pipelines, etc.

Generating observability metrics for data lake usage based on data layer activity logs

Systems and methods for generating augmented search results are disclosed. An example method may be performed by one or more processors of a ranking system and include receiving a search query, generating, for each respective data asset of a plurality of data assets, a query relevancy score indicating a likelihood that the respective data asset is relevant to the search query, retrieving, for each of a number of potentially relevant data assets, a utility score indicating a likelihood that the potentially relevant data asset is useful, generating, for each of the number of potentially relevant data assets, an augmented query score indicating a likelihood that the potentially relevant data asset is relevant to and useful for the search query based on the query relevancy scores and the utility scores, and generating augmented search results for the search query based on the augmented query scores.

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Bengaluru, India

Sreenivasulu Nallapati