Showing 3 open source projects for "patterns"

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  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

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  • Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software. Icon
    Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software.

    Banks, lending institutions

    Founded in 2004, axefinance is a global market-leading software provider focused on credit risk automation for lenders looking to provide an efficient, competitive, and seamless omnichannel financing journey for all client segments (FI, Retail, Commercial, and Corporate.)
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  • 1
    Metacrafter

    Metacrafter

    Metadata and data identification tool and Python library

    Python command line tool and Python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifiable information (PII). Metacrafter is a rule-based tool that helps to label fields of the tables in databases. It scans table and finds person names, surnames, midnames, PII data, basic identifiers like UUID/GUID. These rules written as .yaml files and could be easily extended.
    Downloads: 0 This Week
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  • 2
    DataCleaner

    DataCleaner

    Data quality analysis, profiling, cleansing, duplicate detection +more

    DataCleaner is a data quality analysis application and a solution platform for DQ solutions. It's core is a strong data profiling engine, which is extensible and thereby adds data cleansing, transformations, enrichment, deduplication, matching and merging. Website: http://datacleaner.github.io
    Downloads: 6 This Week
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  • 3
    Roomba

    Roomba

    A Node.js tool to examine the correctness of Open Data Metadata

    Linked Open Data (LOD) has emerged as one of the largest collection of interlinked datasets on the web. Benefiting from this mine of data requires the existence of descriptive information about each dataset in the accompanying metadata. Such meta information is currently very limited to few data portals where they are usually provided manually thus giving little or bad quality insights. To address this issue, we propose a scalable automatic approach for extracting, validating and generating...
    Downloads: 0 This Week
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