Abstract
This research presents a novel Data Analytics Stage Model (DASM) to address the shortcomings of existing models. By
analysing 26 prior models, several key gaps were identified: limited model synthesis, lack of methodological rigor, absence of
legal compliance considerations, and unclear descriptions. DASM offers a comprehensive framework to help organisations
assess their data analytics (DA) maturity, utilising transition tables to understand their developmental path. DASM's standardised
structure and clear definitions provide a valuable tool for organisations seeking to enhance their DA capabilities.
analysing 26 prior models, several key gaps were identified: limited model synthesis, lack of methodological rigor, absence of
legal compliance considerations, and unclear descriptions. DASM offers a comprehensive framework to help organisations
assess their data analytics (DA) maturity, utilising transition tables to understand their developmental path. DASM's standardised
structure and clear definitions provide a valuable tool for organisations seeking to enhance their DA capabilities.
| Original language | English |
|---|---|
| Pages | 152-162 |
| Publication status | Published - 2024 |
| Externally published | Yes |
| Event | ICEB 2024 - Duration: 24 Oct 2024 → … |
Conference
| Conference | ICEB 2024 |
|---|---|
| Period | 24/10/24 → … |