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Researchers from TU Berlin’s Database Systems and Information Management (DIMA) Group and Big Data Management (BigDaMa) Group as well as DFKI’s Intelligent Analytics for Massive Data (IAM) Group participated in the BTW 2019 Data Science Challenge and awarded the 1st place.

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... Zur Erlangung von Datensouveränität benötigen Deutschland bzw. Europa eine nachhaltig (und öffentlich) betriebene Daten- und Analyseinfrastruktur. ... [Markl, V. Informatik Spektrum (2019)].

A pre-print version is available.(in German language).

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Bundeskanzlerin Angela Merkel lud am 29. Mai 2018 zu einem Expertengespräch zum Thema Künstliche Intelligenz (KI) ins Bundeskanzleramt ein. Mit Prof. Dr. Volker Markl (TU Berlin, DFKI) und Prof. Dr. Klaus-Robert Müller (TU Berlin), gehörten gleich zwei Mitglieder des Berlin Big Data Center (BBDC) Managements der Gesprächsrunde an.

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Events

Big Data All Hands Meeting

10. September 2018

Die beiden vom BMBF geförderten Big-Data-Kompetenzzentren, das BBDC und das ScaDS Dresden/Leipzig, organisieren eine 2. gemeinsame Fachtagung im Themenfeld "Big Data" im Smart Data Forum in Berlin. Die Vorstellung ausgewählter Forschungsschwerpunkte und -highlights aus drei Jahren erfolgreicher Arbeit und ein Ausblick auf die Zukunft stehen im Focus.

Summer School for Big Data 2018

2-Jul-2018 until 6-Jul-2018

BBDC and  ScaDS Dresden/Leipzig are organizing the fourth international big data summer school in its series (former events: 20162017). We offer inspiring insights into the diverse fields of big data by selected keynotes from international experts combined with possibilities for practical sessions. The practical sessions start with a Hackathon prior to the actual school start and will be continued during the week in the tutorial-styled sessions.

Both events will take place in the University of Leipzig.

Short News

Workshop on Distributed and Stream Data Processing and ML, March 22, 2019.

International leading experts discuss scalable data analysis and machine learning on distributed data and datastreams from a technical perspective. This is one of the core topics of the BBDC particularly with regard on IoT and industry 4.0. The workshop serves to network and further strengthen the cooperation between the Berlin Big Data Center and leading international researchers.

Please, register now.

Big Data Newsletter Archive

Five Dimensions of Big Data

Big data is often defined as any data set that cannot be handled using today’s widely available mainstream techniques and technologies. The challenges of handling big data are often described using 3-Vs (volume, variety and velocity): high volume of data from a variety of data sources arriving with high velocity analysed to achieve an economic benefit. However, the 3-Vs fail to reflect complexity of “Big Data” in its entirety.

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According to the Harvard Business Review, Data Scientist is “The Sexiest Job of the 21st Century”. Data scientists are often considered to be wizards that deliver value from big data. These wizards need to have knowledge in three very distinct subject areas, namely, scalable data management, data analysis and domain area expertise. However, it is a challenge to find these jacks-of-all-trades that cover all three areas. Or, as the Wall Street Journal puts it “Big Data’s Problem is Little Talent”. Naturally, finding talented data scientists is also a requirement, if we are to put big data to good use. If data analysis were specified using a declarative language, data scientists would not have to worry about low-level programming any longer. Instead, they would be free to concentrate on their data analysis problem. The goal of the Berlin Big Data Center is to help bridge the Talent Gap of Big Data through researching and developing novel technology.

Read more about it in the article of the VLDB keynote "Breaking the Chains: On Declarative Data Analysis and Data Independence in the Big Data Era" by Volker Markl.