« Achieving deep big data analysis will require technological breakthroughs that unite research advances in machine learning and database management systems. »Volker Markl, Director of the BBDC
January 15, 2020
The Berlin Big Data Center (BBDC) and the Berlin Center for Machine Learning (BZML) will merge into the newly established Berlin Center for the Foundations of Learning and Data (BIFOLD).
On 15 January 2020, BBDC Director Prof. Dr. Volker Markl and BZML Director Prof. Dr. Klaus-Robert Müller announced the new AI Competence Center BIFOLD. The offical press conference was held together with Federal Minister of Education and Research (BMBF) Anja Karliczek, Ruling Mayor of Berlin Michael Müller and President of Technische Universität Berlin (TU Berlin) Prof. Dr. Christian Thomsen.
For more information please also see the official press release of BMBF and TU Berlin.
March 23, 2019
The workshop was held at the Smart Data Forum (SDF) showroom in Berlin Charlottenburg. An audience of about 70 people came to hear four insightful presentations on data processing and machine learning.
18. Januar 2019
Mit einem Kick-off-Meeting im Smart Data Forum wurde am 18. Januar die zweite Förderphase des Berlin Big Data Center (BBDC) eingeläutet. Die Pis der jeweiligen Konsortialmitglieder trafen zusammen um in kurzen Vorträgen ihre jeweiligen Forschungsfelder anzureißen und einen Ausblick zu geben, was in der kommende Förderphase im Rahmen der einzelnen Arbeitspakete erforscht und umgesetzt werden soll.
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.
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: 2016, 2017). 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.
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 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.
Big Data Newsletter Archive
The Big Data Research 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). Since Smart Data Forum endet in August 2019, the Big Data Research Newsletter has been discontinued.
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.
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 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.