Data-intensive software systems are generally made of a database (sometimes in the form of a set of files) and a collection of application programs in strong interaction with the former. They constitute critical assets in most enterprises, since they support business activities in all production and management domains. Data-intensive systems form most of the so-called legacy systems: they typically are one or more decade old, they are very large, heterogeneous and highly complex. Many of them significantly resist modifications and change due to the lack of documentation, to the use of aging technologies and to inflexible architectures. Therefore, the evolution of data-intensive systems clearly calls for automated support. This thesis particularly explores the use of automated program analysis and transformation techniques in support to the evolution of the database component of the system. The program analysis techniques aim to ease the database evolution process, by helping the developers to understand the data structures that are to be changed, despite the lack of precise and up-to-date documentation. The objective of the program transformation techniques is to support the adaptation of the application programs to the new database. This adaptation process is studied in the context of two realistic database evolution scenarios, namely database platform migration and database schema refactoring.