How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science
| Title | How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science |
| Publication Type | Book Chapter |
| Year of Publication | 2018 |
| Authors | Amato, G, Candela, L, Castelli, D, Esuli, A, Falchi, F, Gennaro, C, Giannotti, F, Monreale, A, Nanni, M, Pagano, P, Pappalardo, L, Pedreschi, D, Pratesi, F, Rabitti, F, Rinzivillo, S, Rossetti, G, Ruggieri, S, Sebastiani, F, Tesconi, M |
| Secondary Authors | Flesca, S, Greco, S, Masciari, E, Saccà, D |
| Book Title | A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years |
| Pagination | 287 - 306 |
| Publisher | Springer International Publishing |
| City | Cham |
| ISBN Number | 978-3-319-61893-7 |
| Abstract | During the last 35 years, data management principles such as physical and logical independence, declarative querying and cost-based optimization have led to profound pervasiveness of relational databases in any kind of organization. More importantly, these technical advances have enabled the first round of business intelligence applications and laid the foundation for managing and analyzing Big Data today. |
| URL | https://link.springer.com/chapter/10.1007%2F978-3-319-61893-7_17 |
| DOI | 10.1007/978-3-319-61893-7_17 |