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The Excel Data Mining Add-in. Applications in audit and financial reports

Author

Listed:
  • Daniel HOMOCIANU

    (Alexandru Ioan Cuza” University of Iasi, Romania)

  • Dinu AIRINEI

    (Alexandru Ioan Cuza University of Iasi, Romania)

Abstract

Performance reasons in decision making based on business data usually requires a good management of multiple data formats and also processing speed, flexibility, portability, automation, power of suggestion and ease of use. The paper comes with theoretical ideas and practical examples in favor of using the Excel Data Mining Add-in’s for the aforementioned reasons. Most of the examples include figures linked to video scenarios constructed by the authors and part of an interactive online list with eighteen pieces. Together they contribute to understanding most of the requirements to fulfill in order to have valid examples and useful results

Suggested Citation

  • Daniel HOMOCIANU & Dinu AIRINEI, 2017. "The Excel Data Mining Add-in. Applications in audit and financial reports," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 15(147), pages 451-451.
    • Handle: RePEc:aud:audfin:v:15:y:2017:i:147:p:451
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    File URL: http://revista.cafr.ro/temp/Article_9546.pdf
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    References listed on IDEAS

    as
    1. Dinu AIRINEI & Daniel HOMOCIANU, 2009. "The Geographical Dimension Of Dss Applications," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 637-642, November.
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    1. Dinu Airinei & Daniel Homocianu, 2011. "Meanings Of The Global Business Intelligence," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 2011, pages 237-243, july.
    2. Daniel Homocianu & Dinu Airinei, 2022. "PCDM and PCDM4MP: New Pairwise Correlation-Based Data Mining Tools for Parallel Processing of Large Tabular Datasets," Mathematics, MDPI, vol. 10(15), pages 1-27, July.

    More about this item

    Keywords

    business and financial data; spreadsheets; Data Mining (DM); examples;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing

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