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Full-Text Articles in Physical Sciences and Mathematics
Big Data Analytics On Cloud: Challenges, Techniques And Technologies, Aleksander Biberaj, Olimpion Shurdi, Bledar Kazia, Renalda Kushe, Alban Rakipi
Big Data Analytics On Cloud: Challenges, Techniques And Technologies, Aleksander Biberaj, Olimpion Shurdi, Bledar Kazia, Renalda Kushe, Alban Rakipi
UBT International Conference
These days it is known that Big Data Analytics is taking a huge attention from researchers and also from business. We all are witness of the data growth that every institution, company or even individuals store in order to use them in the future. There is a big potential to extract useful data from this Big Data that is stored usually in Cloud because sometimes there is not enough local space to store big amounts of data. There is a huge number of sectors where Big Data can be helpful including economic and business activities, public administration, national security, scientific …
Performance Evaluation Of Non-Relational Data On Big Data Environments, Edmond Jajaga, Edi Hasaj
Performance Evaluation Of Non-Relational Data On Big Data Environments, Edmond Jajaga, Edi Hasaj
UBT International Conference
Big data management is a real challenge for traditional systems. The experimental evaluation is performed on measurement of performance of five different databases with an open non-relational dataset. It was structured and tested separately in each store, giving some advantages and limitations to them from a practical point of view. The results are drawn based on the throughput per number of users executed respectively. It was loaded and executed more than a million of records in each and every database. Following its semi-persistent model, Redis performed better than other databases.
The Importance Of Big Data Analytics, Eljona Proko
The Importance Of Big Data Analytics, Eljona Proko
UBT International Conference
Identified as the tendency of IT, Big Data gained global attention. Advances in data analytics are changing the way businesses compete, enabling them to make faster and better decisions based on real-time analysis. Big Data introduces a new set of challenges. Three characteristics define Big Data: volume, variety, and velocity. Big Data requires tools and methods that can be applied to analyze and extract patterns from large-scale data. Companies generate enormous volumes of poly-structured data from Web, social network posts, sensors, mobile devices, emails, and many other sources. Companies need a cost-effective, massively scalable solution for capturing, storing, and analyzing …
Exploring The Role Of Sentiments In Identification Of Active And Influential Bloggers, Mohammad Alghobiri, Umer Ishfaq, Hikmat Ullah Khan, Tahir Afzal Malik
Exploring The Role Of Sentiments In Identification Of Active And Influential Bloggers, Mohammad Alghobiri, Umer Ishfaq, Hikmat Ullah Khan, Tahir Afzal Malik
UBT International Conference
The social Web provides opportunities for the public to have social interactions and online discussions. A large number of online users using the social web sites create a high volume of data. This leads to the emergence of Big Data, which focuses on computational analysis of data to reveal patterns, and associations relating to human interactions. Such analyses have vast applications in various fields such as understanding human behaviors, studying culture influence, and promoting online marketing. The blogs are one of the social web channels that offer a way to discuss various topics. Finding the top bloggers has been a …
The Importance Of Big Data Analytics, Eljona Proko
The Importance Of Big Data Analytics, Eljona Proko
UBT International Conference
Identified as the tendency of IT, Big Data gained global attention. Advances in data analytics are changing the way businesses compete, enabling them to make faster and better decisions based on real-time analysis. Big Data introduces a new set of challenges. Three characteristics define Big Data: volume, variety, and velocity. Big Data requires tools and methods that can be applied to analyze and extract patterns from large-scale data. Companies generate enormous volumes of polystructured data from Web, social network posts, sensors, mobile devices, emails, and many other sources. Companies need a cost-effective, massively scalable solution for capturing, storing, and analyzing …