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Summary

Innovative IT novice offering his full knowledge and experience to deliver highly effective and creative solutions to technology challenges. Highly organized with strong capacity to prioritize workload and always trying to preform within deadlines.  


Projects 

Sept 2016Jan 2017

VarazdinEvents iOS application

App Start Contest

Successfully implemented and delivered application written in Swift.

Jan 2016Present

Android Application TKDtracer

Dec 2015Present

Distributed Databases

Final work about distributed databases in Apache Cassandra. 

Certifications

July2016

M102: MongoDB for DBAs

Completed as the top 10% of all students
Jan 2016

Successful presentation of application TKDtracer

Infinum

Prototype of Android Application TKDtracer

Dec 2015

Microsoft Technology Associate: Database Administration Fundamentals

Microsoft, License 90045188

Education 

Sep 2016Sep 2018

mag.inf.

Faculty of organization and informatics

In order to enroll,  course "Database and Knowledge Bases"

Sep 2013Sep 2016

bacc.inf. 

Faculty of organization and informatics

Experience

November 2016Now

Big Data developer

NTH Mobile

Setting up cluster which will handle fault-tolerance, availability, NRT and Real-Time data processing. 

HDP is giving ability to not only setting up cluster with key components but also ability to monitor whole cluster much easily. Confluent upon Kafka which gives kafka-connect another dimension with avro schema but also with huge amount of source and sink connectors. Configured Landoop UIs allowing easily tracking Kafka topics and it data, schema registries and also ability to manipulate the connectors.Cassandra brings availability, fault tolerance + brilliant performance under large sets of data.

With HBase we accomplished the main benefits over NoSQL data store solutions. His ability to quickly store and access sparse data is allowing in architecture to provide NRT random R/W upon Hadoop. 

July 2016Sept 2016

Database developer Intern

Farmeron

Testing throughput and latency of Apache Cassandra on Multi-node Cluster using Apache Spark as engine for big data processing. Also trying to compare the same results with Microsoft SQL Server performance.
The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data.

Also was testing performance of Hadoop multi-node cluster configuration with Apache Drill and Zookeeper along with.

Contributor

Nov2017

Stream Reactor 0.2.4-3.1.1v

https://github.com/datamountaineer/stream-reactor

Created kafka-connect-hbase-sink for Hortonworks Data Platform v2.6 which has HBase v1.1.2 (by then, was available sinker for HBase v1.2)