The main objective of this course is acquiring the knowledge and skills needed to design, implement and analyze Big Data services. The course is intended to provide a basic understanding of the issues and problems involved in service oriented approach for Big Data environments, a knowledge of currently practical techniques for satisfying the needs of such a system, and an indication of the current research approaches that are likely to provide a basis for tomorrow’s solutions. The course will focus on models, methods, techniques, algorithms for designing, implementing and analyzing Big Data services. Hadoop/Spark ecosystem and NoSQL system will be used as tools/standards for creating services that can process very large amounts of data. The course material will be drawn from textbooks as well as recent research literature. The following topics will be covered: distributed systems models, applications for Big Data, service-oriented architecture, Microservices, Big Data, Hadoop ecosystem, in-memory computing (Apache Spark) Big Data real-time and stream processing (Storm), data storage services for Big Data, Big Data analytics and ethical issues on Big Data. The course presents theoretical models and general techniques for Big Data processing and storage together with practical examples and use cases. The course offers a service-based approach for Big Data and ethical issues. By providing a balanced view of theory and practice, the project should allow the student to understand use, and build practical Big Data systems for data processing (e.g. Big Data analytics) and Big Data storage services.

Cursul abordează capitole importante pentru domeniul Cloud Computing, urmărind studiul și analiza caracteristicilor sistemelor Cloud. Studiul se va baza pe o selecție de articole care au avut un impact semnificativ asupra evoluției acestora, sau care prezintă idei actuale aflate în studiu sau în evaluare, cu un impact previzibil în viitor.