Ova lekcija opisuje softversko okruženje za obradu velikih količina podataka Apache Hadoop, njegove komponente koji upotpunjavaju i proširuju mogućnosti Hadoop-a, kao i njegovo korištenje u praksi. Da bismo u potpunosti razumeli prednosti Hadoop-a, potrebno je sagledati najpre razliku između paralelnog i distribuiranog računanja, načine čuvanja (HDFS arhitekturu), upravljanje resursima i procesiranja podataka, princip horizontalne skalabilnosti, itd.

The PLATOON Data Analytics toolbox is formed of all the data analytics tools that are developed and validated for the different use cases of the project. These tools will allow the extraction of value from heterogeneous data sources. There will be two main groups of data analytics tools:

The European electricity system undergoes significant changes driven by the European Union (EU) common rules for the internal market for electricity, as well as by the climate action agenda. The European Green Deal is also an opportunity for modernizing the energy system in order to make it competitive and sustainable with regard to the environment.

Data in the energy domain grows at unprecedented rates and is usually generated by heterogeneous energy systems.
Despite the great potential that big data-driven technologies can bring to the energy sector, general adoption is still lagging. Several challenges related to controlled data exchange and data integration are still not wholly achieved. As a result, fragmented applications are developed against energy data silos, and data exchange is limited to few applications.

Artificial Intelligence (AI) is the pinnacle of digitalization; AI is revolutionizing how we work and live. We now have more data than ever about our business processes, and Deep Learning, in particular, gives us the tools to create real value from our data. With AI, we can improve our processes' efficiency; we can improve quality or do completely new things by creating new business models. With AI, computers can understand audio and text in natural language, allowing them to create new user experiences.

Challenges for Transforming Big data into Knowledge: Precision Medicine- A Use Case

This is akeynote lecture from prof. Maria-Esther Vidal Scientific Data Management Group TIB

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This is a Keynote Lecture delivered at the Big Data Analytics Summer School 2019 by Prof. Dr. Sören Auer.

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This is a Keynote Lecture delivered at the Big Data Analytics Summer School 2019 by Atanas Kiryakov, the Founder and CEO of Ontotext a Semantic Web pioneer, and leading developer of semantic technology and knowledge graphs.

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This is a Keynote Lecture delivered at the Big Data Analytics Summer School 2020 by Dr Gloria Bordogna, Italian National Research Council IREA

This is a Lecture delivered at the Big Data Analytics Summer School 2020 by Dr. Simon Scerri, Fraunhofer IAIS.