Semantic information infrastructures from business information delivery to water management
This is a Keynote Lecture delivered at the Big Data Analytics Summer School 2020 by Dr. Mariana Damova, Mozajka.
Apache Kafka
Apache Kafka is a distributed messaging system that uses the publish-subscribe mechanism. It was developed to support continuous and resilient messaging with high throughput at LinkedIn. Kafka is a fast, scalable, durable, and fault-tolerant system. It maintains feeds of messages in categories called topics. These topics are used to store messages from the producers and deliver them to the consumers who have subscribed to that topic.
Big Data Analytics Summer School, Belgrade, Serbia, June 2020
Organizing Committee
- Valentina Janev, Institute Mihajlo Pupin, Serbia
- Damien Graux, Fraunhofer IAIS, Germany
- Hajira Jabeen, University of Bonn, Germany
- Emanuel Sallinger, University of Oxford, UK
About the School
One of the objectives of the LAMBDA project is organization of a Big Data Analytics Summer School in Belgrade in 2019 and 2020.
Data for AI: Foresight
This is a Lecture delivered at the Big Data Analytics Summer School 2020 by Dr. Simon Scerri, Fraunhofer IAIS.
Predictive Analytics in Renewable Energy Systems
With the aim of improving ecological interest, the share of renewable energy sources (RES) in energy production has to be increased. Nonetheless, that growth adversely influences the grid’s instability, as a result of the dependency between the RES production and weather conditions.
Survey on Big Data Tools
This introductory lecture discusses the Big Data processing pipeline and the Big Data Landscape from the following perspectives
- Big Data Frameworks
- NoSQL Platforms and Knowledge Graphs
- Stream Processing Data Engines
- Big Data Preprocessing
- Big Data Analytics
- Big Data Visualization Tools.
Overview and Comparison of Machine Learning Algorithms
Big Data Analytics is a crucial component of the Big data paradigm and refers to the process of extracting useful knowledge from large datasets or streams of data. Due to enormity, high dimensionality, heterogeneous, and distributed nature of data, traditional techniques of data mining may be unsuitable to work with big data.
SCADA Intrusion Detection Systems
Specific intrusion detection systems (IDSs) are needed to secure modern supervisory control and data acquisition (SCADA) systems due to their architecture, stringent real-time requirements, network traffic features and specific application layer protocols. This lecture aims to contribute to assess the state-of-the-art, identify the open issues and provide an insight for future study areas. To achieve these objectives, we start from the factors that impact the design of dedicated intrusion detection systems in SCADA networks and focus on network-based IDS solutions.
