News

Creativity is a professors crucial characteristic. In this fall Prof. Müller refreshes his out-of-the-box thinking with a sabbatical. The co-director of the BBDC uses the time to meet leading...

Read more

Prof. Dr. Stephan Günnemann, Technical University of Munich

Date: 28-Nov-2016 , 2pm

Location: DFKI Projektbüro Berlin, 4th Floor, Room: Weizenbaum, Alt-Moabit 91 C, 10559 Berlin

Read more

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.

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.

Opens internal link in current windowRead the full article

Data Scientist - Bridging the Talent Gap

According to the Opens external link in current windowHarvard 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 Opens external link in current windowWall 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 "Opens external link in current windowBreaking the Chains: On Declarative Data Analysis and Data Independence in the Big Data Era" by Volker Markl.