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Showing 1 to 4 of 4 for “"data profiling"”.

  1. Data profiling - efficient discovery of dependencies

    Data profiling is the computer science discipline of analyzing a given dataset for its metadata. The types of metadata range from basic statistics, such as tuple counts, column aggregations, and value distributions, to much more complex structures, in particular inclusion dependencies (INDs), …

    potsdam-diss Repository record for Data profiling - efficient discovery of dependencies (opens in a new tab)

  2. Locating cache performance bottlenecks using data profiling

    Effective use of CPU data caches is critical to good performance, but poor cache use patterns are often hard to spot using existing execution profiling tools. Typical profilers attribute costs to specific code locations. The costs due to frequent cache misses on a given piece of data, however, may …

    mit Repository record for Locating cache performance bottlenecks using data profiling (opens in a new tab)

  3. Unveiling data quality dynamics in online retail: An exploration of product attributes

    Data quality is essential for effective predictive analytics and operational efficiency in e-commerce. This study investigates the quality of product attribute data such as size, colour, style, and gender classification within an online retail environment, where inaccurate or incomplete attributes …

    western-cape Repository record for Unveiling data quality dynamics in online retail: An exploration of product attributes (opens in a new tab)

  4. A Semi-Supervised Predictive Model to Link Regulatory Regions to Their Target Genes

    … technologies have provided us with a wealth of data profiling a diverse range of biological processes. In an effort to better understand the process of gene regulation, two predictive machine learning models specifically tailored for analyzing gene transcription and polyadenylation are …

    duke Repository record for A Semi-Supervised Predictive Model to Link Regulatory Regions to Their Target Genes (opens in a new tab)