Utilizing the data mesh paradigm to address ESG data management challenges
- Environmental, social, and governance (ESG) data are increasingly critical for organizations, given their growing importance based on business and regulatory requirements. However, managing ESG data presents unique challenges due to their complexity and the diverse sources from which they are generated. Traditional centralized data architectures often struggle to meet these demands, leading to issues such as scalability limitations, data silos, and bottlenecks in data collection. Centralized systems also lack the flexibility to accommodate domain-specific knowledge, which is crucial for interpreting ESG data accurately.
| Author of HS Reutlingen | Feierabend, David; Schlegel, Dennis |
|---|---|
| DOI: | https://doi.org/10.1201/9781003528951-5 |
| ISBN: | 978-1-003-52895-1 |
| Published in: | Digital project practice for green finance and ESG innovation |
| Publisher: | Auerbach |
| Place of publication: | New York |
| Editor: | Tobias Endress |
| Document Type: | Book chapter |
| Language: | English |
| Publication year: | 2026 |
| Edition: | 1 |
| Page Number: | 17 |
| First Page: | 82 |
| Last Page: | 98 |
| PPN: | Im Katalog der Hochschule Reutlingen ansehen |
| DDC classes: | 004 Informatik |
| Open access?: | Nein |
| Licence (German): |  In Copyright - Urheberrechtlich geschützt |
