Abstract
Generating value from big data is a task that requires models’ preparation and use of advanced technologies but which, above all, is based on the ability to extract, manage and analyse data. These processes’ effectiveness depends on the data's quality and their structured or unstructured nature. We are witnessing a growing number of applications based on unstructured data mining in the accounting and management fields. This research aims to demonstrating that despite the traditional association between accounting and quantitative analyses (expected to be based mainly on structured financial data). The findings show that several useful applications now rely on unstructured data in this field. A basic analysis of the cybersecurity risks is also presented, along with mitigating strategies to allow companies to comply with current regulations such as the GDPR. The result might appear surprising from the business perspective, but it is not from a data science perspective. In conclusion the growing number of unsctructured data business applications should orientate a better understanding of their potential and target better training of finance specialist on data processing skills.
Original language | English |
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Title of host publication | ICCBDC '22: Proceedings of the 2022 6th International Conference on Cloud and Big Data Computing |
Publisher | ACM |
Pages | 37-41 |
Number of pages | 5 |
ISBN (Electronic) | 9781450396578 |
ISBN (Print) | 978-1-4503-9657-8 |
DOIs | |
Publication status | Published - 18 Oct 2022 |
Event | 6th International Conference on Cloud and Big Data Computing - Birmingham, United Kingdom Duration: 18 Aug 2022 → 20 Aug 2022 https://dl.acm.org/doi/proceedings/10.1145/3555962 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 6th International Conference on Cloud and Big Data Computing |
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Abbreviated title | ICCBDC 2022 |
Country/Territory | United Kingdom |
City | Birmingham |
Period | 18/08/22 → 20/08/22 |
Internet address |
Bibliographical note
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- Applications
- Structured data
- Accounting
- Big Data
- Management
- Unstructured data
- Analytics