Showing 6 open source projects for "qgis-osgeo4w-2.6.1-1-setup"

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  • 1
    Swiple

    Swiple

    Swiple enables you to easily observe, understand, validate data

    Swiple is an automated data monitoring platform that helps analytics and data engineering teams seamlessly monitor the quality of their data. With automated data analysis and profiling, scheduling and alerting, teams can resolve data quality issues before they impact mission critical resources. Experience hassle-free integration with Swiple's zero-infrastructure and zero-code setup. Seamlessly incorporate data quality checks into your existing workflows without any coding or infrastructure...
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  • 2
    Population Shift Monitoring

    Population Shift Monitoring

    Monitor the stability of a Pandas or Spark dataframe

    popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets. popmon creates histograms of features binned in time-slices, and compares the stability of the profiles and distributions of those histograms using statistical tests, both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher-dimensional, e.g. it can also track correlations between any two...
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  • 3
    DISTOD

    DISTOD

    Distributed discovery of bidirectional order dependencies

    The DISTOD data profiling algorithm is a distributed algorithm to discover bidirectional order dependencies (in set-based form) from relational data. DISTOD is based on the single-threaded FASTOD-BID algorithm [1], but DISTOD scales elastically to many machines outperforming FASTOD-BID by up to orders of magnitude. Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. They can express that, for example, sorting books...
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  • 4
    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...
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  • 5
    A Data profiling project
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  • 6
    COBOL Data Definitions
    Parse, analyze and -- most importantly -- use COBOL data definitions. This gives you access to COBOL data from Python programs. Write data analyzers, one-time data conversion utilities and Python programs that are part of COBOL systems. Really.
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