Understanding Big Data using Hadoop
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ABSTRACT
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As technology progresses and devices become more 
interconnected ("Internet of Things"), emerges 
the need to analyze the large amounts of information
generated by these devices, with the aim to obtain 
relevant metrics and data. 
According to some analyses, it is estimated that 
the global data volume will exceed 40 billion terabytes 
by 2020. 
Hadoop, a project initiated by Google and that became 
open-source, aims to solve this problem in a distributed 
mode. 
The presentation highlights the main issues that arise in 
analyzing these amounts of data in distributed systems, 
describes briefly how the Hadoop system works and what 
related technologies exist (Pig, Hive).

Contents:
-What and where is Big Data
-Practical applications of Big Data
-Hadoop design and components
-What is HDFS
-How MapReduce works
-Similar technologies and examples
          
SPEAKER(S)
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Filip GODINA
UniCredit Business Integrated Solutions
Italia, Romania
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Filip Godina
Senior Technical Analyst

Wide experience in web development and working with 
Big Data (Java, Scala, C/C++, most scripting languages, 
HTML/CSS/Javascript), working with Hadoop, databases 
and networks. I have over 8 years experience and 
I've worked at multiple companies in various fields 
where I gained a lot of experience with many different 
technologies, having learned the benefits and drawbacks 
of each. I love to optimize systems, big or small. 
Distributed computing is one of my main interests and 
I'm always ready to solve a challenging scalability 
problem especially if new or open-source technologies 
are involved.
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