About The Conference
What is DataMass?
It’s not just another conference. It’s an event created with passion – and targeted at those who use Big Data in practice in their everyday work. The main idea behind the conference is to promote knowledge and experience in designing and implementing tools for the analysis of big data volumes.
We connect the people who care
We believe that building a community of dedicated experts will help us share knowledge and exchange experience in shaping scalable and distributed computing solutions.
We value real-life expertise – is there any better way to learn than from actual specialists? Our speakers, true practitioners from top data-driven companies, will show you what they have learned and discovered about the Big Data world.
Answering your needs
Playing an active role in the Big Data world, we could see that a big technical conference focused on the exchange of knowledge and experience in this field was needed in Poland. The aim of DataMass is to create a synergy between businesses focused on the creation and implementation of Enterprise-class solutions, together with experience and knowledge of the academic environment. The Data Science meetup in Gdańsk is a tangible proof that this is currently possible.
Callbacks from Datamass 2017
While many technical conferences present the theory of whatever technology they cover, it was great to see that both the organizers and the speakers of DataMass paid attention to the practical part above all. Theory is one thing, but the implementation of it is a whole new experience – and it’s great to have an event that gives big data professionals space to present their work.
TidK, MVP Microsoft
It’s amazing to see that Big Data is becoming more and more popular as numerous meetups and conferences spring up all across Europe. Gdańsk needed an event like that, and I believe that DataMass is a great occasion for those who use big data to meet other experts and enthusiasts and chat about their experiences and lessons learned.
Balazs Ferenc Gaspar
Being a speaker at the first-ever DataMass Summit was a fantastic experience. Not only was it an occasion to exchange knowledge with other professionals from the field, but also a great opportunity to see how the community of big data enthusiasts is growing and developing. Combining great fun with practical knowledge is the key to a successful event of this type – and the organizers managed to do it.
Jakub Nowacki, PhD
DataMass Summit 2017 was the first edition of the conference and definitely not just another conference of this kind. How was it different? First of all – the venue. It took place in a post-industrial shipyard building. Not a very typical place to hold a technical conference, but it worked! Secondly, the conference was purely practical. Speakers focused on their experience, and not just the theoretical part, which in turn gives a lot of space for others to learn.
Video about DataMass 2017
Meet our awesome Sponsors!
Hadoop Application Development
Creation of distributed computing solutions using Hadoop framework. Architecture, implementation and testing of software based on a cluster or a distributed system of files. Creation of ETL processes and reporting systems.
Hadoop in R&D centers
Cluster solutions in R&D centres. One of the examples is the use of the platform for computing in grant-funded activities at technical universities. We show how a cluster may be used for advance computing and modelling.
Hadoop in business
Business application of Big Data tools. Typical using case studies showing why the world of big data wins the market all over the world. Pros and cons of solutions in terms of efforts and costs related to the implementation and maintenance of such environments. Reference to commercial vs. open-source technologies.
Real-time processing of data going to a cluster. This form of data analysis enables an immediate response to any generated activity. It is not only about the activity generated by users themselves, but also about devices communicating with each other within the IoT standard.
Data Science, Analytics and Reporting
Data analysis systems using machine learning and artificial intelligence. Creation and optimisation of analytically sophisticated solutions. Methods of modelling and verifying developed solutions.
Management and administration of clusters based on BigData technologies. In this subject, we focus on issues related to the installation and maintenance of advance cluster solutions (installation, configuration, decomposition and update of the cluster). This cycle also touches upon the methods of automating maintenance processes within the cluster.