Prof. Marco Brambilla

Argomenti del programma: The course content is organized in three main chapters: 1. Approaches to Big Data management Big Data problems and dimensions Data engineering and data science pipeline Enterprise-scale data management Scalability and persistency vs. volatility issues Cross-source data integration problems and architectures CAP theorem and implications.

Argomenti del programma: The course content is organized in three main chapters: 1. Approaches to Big Data management Big Data problems and dimensions Data engineering and data science pipeline Enterprise-scale data management Scalability and persistency vs. volatility issues Cross-source data integration problems and architectures CAP theorem and implications.

Argomenti del programma: The course content is organized in three main chapters: 1. Approaches to Big Data management Big Data problems and dimensions Data engineering and data science pipeline Enterprise-scale data management Scalability and persistency vs. volatility issues Cross-source data integration problems and architectures CAP theorem and implications.

Argomenti del programma: The course content is organized in three main chapters: 1. Approaches to Big Data management Big Data problems and dimensions Data engineering and data science pipeline Enterprise-scale data management Scalability and persistency vs. volatility issues Cross-source data integration problems and architectures CAP theorem and implications.

Argomenti del programma: The course content is organized in three main chapters: 1. Approaches to Big Data management Big Data problems and dimensions Data engineering and data science pipeline Enterprise-scale data management Scalability and persistency vs. volatility issues Cross-source data integration problems and architectures CAP theorem and implications.