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Data profiling tool Desbordante enhanced with new dependency discovery techniques · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Two new research papers explore advancements in data profiling techniques, focusing on the Desbordante tool. The first paper details optimizations for order dependency discovery algorithms, achieving up to a 10x performance improvement and reduced memory consumption. The second paper introduces support for Probabilistic Functional Dependency (pFD) discovery within Desbordante, analyzing its relationship with Approximate Functional Dependencies (AFDs) and comparing their performance. AI

IMPACT Enhances data profiling capabilities, potentially improving database query optimization, data cleaning, and anomaly detection.

RANK_REASON The cluster contains two academic papers published on arXiv detailing new algorithms and implementation techniques for data profiling tools.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Data profiling tool Desbordante enhanced with new dependency discovery techniques · 2 sources tracked

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The cluster contains two academic papers published on arXiv detailing new algorithms and implementation techniques for data profiling tools.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yakov Kuzin, Dmitriy Shcheka, Michael Polyntsov, Kirill Stupakov, Mikhail Firsov, George Chernishev ·

    Order in Desbordante: Techniques for Efficient Implementation of Order Dependency Discovery Algorithms

    arXiv:2607.23632v1 Announce Type: cross Abstract: Science-intensive data profiling focuses on discovery and validation of various patterns in datasets. This study considers discovery of one such pattern - order dependency (OD). Simply put, OD states that some list of columns is o…

  2. arXiv cs.AI TIER_1 English(EN) · Ilia Barutkin, Maxim Fofanov, Sergey Belokonny, Vladislav Makeev, George Chernishev ·

    Extending Desbordante with Probabilistic Functional Dependency Discovery Support

    arXiv:2607.23636v1 Announce Type: cross Abstract: Data profiling aims to extract complex patterns from data for further analysis and use that data in domains such as data cleaning, data deduplication, anomaly detection, and many more. Functional dependencies (FDs) are one of the …

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