With Cloud Computing and Big Data Research Laboratory (B3LAB) “Big Data Analysis Solutions”, valuable information can be extracted by processing and analyzing large amounts of data in different forms. SAFİR Big Data; offers big data storage, data transfer and analytics solutions that are easy to install and use. With the installation made on the servers in the B3LAB Prototype Data Center, physically; Big data infrastructure can be used virtually with the services on SAFİR Infrastructure. Both installations SAFİR Big Data; enables the processing of batch and streaming data with scalable, high available, distributed and redundant infrastructure.
SAFİR Big Data; provides solutions in big data, data transfer and processing, big data analytics, big data ecosystem training, proof of concept (PoC) applications.
Hadoop cluster installation, configuration, management and optimization within the scope of big data architecture solutions; operating system configuration and optimization used; big data file systems configuration and optimization; Big data network architecture design and installation studies are carried out.
Within the scope of data flow and processing solutions; streaming data management and processing, batch data transfer, management and processing, NoSQL databases installation and configuration and optimization.
Anomaly detection, estimation, classification and cluster analysis are performed within the scope of big data analytical solutions. More sophisticated systems for fraud prevention can be developed with big data analytics and machine learning.
Training on big data technologies, big data analytics and machine learning is provided. The trainings are supported by application studies on clusters prepared in virtual big data environment on SAFİR Infrasturucture.
By using SAFİR Big Data infrastructure; data center monitoring and estimation of server loads, automatic category assignment to call center records, creation of a genomic variation analysis platform, examination failure root cause analysis for students, information about the growth rate and structure of the data, and big data infrastructure and tools needs analysis studies were carried out.