Nowadays, data and information are becoming more and more important for companies whether it concerns their collection, storage, processing, or reporting. This thesis aims to highlight how technologies have evolved with market needs and how providers have succeeded in adapting or not to these challenges. Text mining was used to extract relevant information on this subject from Gartner reports on Business Intelligence & Analytics Platforms. It turned out to be effective and brought out insights that correspond to other papers related to the subject, which confirms the truthfulness of the topics that the tool brings out. The conclusion is that the market has evolved from segmented offers including traditional OLAP tools towards cloud, augmented capacity and artificial intelligence technologies, provided mainly by large players such as IBM, Microsoft, or Tableau.
| Date of Award | 1 Sept 2022 |
|---|
| Original language | English |
|---|
| Awarding Institution | |
|---|
| Supervisor | Isabelle Linden (Supervisor) |
|---|
- Business Intelligence
- Data
- Text Mining
- Topic Modeling
- Evolution
- Gartner
Evolution of the Business Intelligence industry between 2006 and 2020: A Study on Gartner reports using Text Mining Analytics
BLANCHY, T. (Author). 1 Sept 2022
Student thesis: Master types › Master in Business Engineering Professional focus in Data Science