DataMass Gdańsk Summit
We create an event targeted at people who use Big Data in practice in their daily work. We want to share knowledge and exchange experience in shaping scalable and distributed computing solutions. The main idea behind the conference is to promote knowledge and experience in designing and implementing tools for the analysis of big data volumes.
Playing an active role in the BigData world, we can see that a big technical conference focused on the exchange of knowledge and experience in this field is needed in Poland. The aim of the conference is to create a synergy between businesses, focused on the creation and implementation of Enterprise class solutions, and experience and knowledge of academic environment. The Data Science is a great example showing this is currently possible.
- 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 Administration - 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
- 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
- Real-Time Processing - 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
- 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