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News

We are pleased to announce that the demonstration proposal "Fault-Tolerance for Distributed Iterative Dataflows in Action," by Chen Xu, Rudi Poepsel Lemaitre, Juan Soto, and Volker Markl has been accepted for publication in Issue 12 of PVLDB and for demonstration at the VLDB 2018 Conference, which will be held in Rio de Janeiro, Brazil, from August 27 through August 31, 2018.

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On 26 February, BBDC Director Prof. Dr. Volker Markl and QCRI Executive Director Dr. Ahmed Elmagarmid signed a memorandum of understanding between the two research institutions. MoU will promote collaboration via an exchange of research, academic materials, faculty and research scholars.

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Prof. Volker Markl offered a presentation "Benefits and Potential Risks in Data Analytics Research" at the the Freedom and Responsibility in IT Sciences Leopoldina Workshop.

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Events

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.

Big Data Excellence in Germany and UK

March 1st, 2017 in Berlin

A joint event by the Berlin Big Data Center and UK Science and Innovation Network took place at Smart Data Forum.

The First Berlin Big Data Center Symposium Held in Berlin

The Berlin Big Data Center held its first Symposium on November 8th at the Smart Data Forum, located in Berlin. At this event, members of the BBDC presented the project’s interim results from two years of research.

The Big Data Newsletter

The joint newsletter Big Data Research reflects works done by Berlin Big Data Center (BBDC), Dresden/Leipzig Competence Center for Scalable Data Services and Solutions (ScaDS), Smart Data Innovation Lab (SDIL), Smart Data Forum (SDF), and the project "Assessing Big Data" (Abida).

Edition #001 (Nov 2016)

Edition #002 (Feb 2017)

Edition #003 (July 2017)

Edition #004 (Nov 2017)

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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.

Read the full article

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.