Database Systems Journal, Vol. VI, Issue 3/2015
|
1. Exploring Data in Human Resources Big Data (p. 3-10)Adela BARA, University of Economic Studies, Bucharest, RomaniaIuliana BOTHA, University of Economic Studies, Bucharest, Romania Anda BELCIU, University of Economic Studies, Bucharest, Romania Bogdan NEDELCU, University of Economic Studies, Bucharest, Romania |
|
Nowadays, social networks and informatics technologies and infrastructures are constantly developing and affect each other. In this context, the HR recruitment process became complex and many multinational organizations have encountered selection issues. The objective of the paper is to develop a prototype system for assisting the selection of candidates for an intelligent management of human resources. Such a system can be a starting point for the efficient organization of semi-structured and unstructured data on recruitment activities. The article extends the research presented at the 14th International Conference on Informatics in Economy (IE 2015) in the scientific paper "Big Data challenges for human resources management".
Keywords: Big Data, Business Intelligence, NoSQL Databases, Data Mining, Cloud Computing. |
2. Electricity tariff systems for informatics system design regarding consumption optimization in smart grids (p. 11-18)Simona Vasilica OPREA, University of Economic Studies, Bucharest, Romania |
|
High volume of data is gathered via sensors and recorded by smart meters. These data are processed at the electricity consumer and grid operators' side by big data analytics. Electricity consumption optimization offers multiple advantages for both consumers and grid operators. At the electricity customer level, by optimizing electricity consumption savings are significant, but the main benefits will come from indirect aspects such as avoiding onerous grid investments, higher volume of renewable energy sources' integration, less polluted environment etc. In order to optimize electricity consumption, advanced tariff systems are essential due to the financial incentive they provide for electricity consumers' behaviour change. In this paper several advanced tariff systems are described in details. These systems are applied in England, Spain, Italy, France, Norway and Germany. These systems are compared from characteristics, advantages/disadvantages point of view. Then, different tariff systems applied in Romania are presented. Romanian tariff systems have been designed for various electricity consumers' types. Different tariff systems applied by grid operators or electricity supplierswill be includedin the database model that is part of an informatics system for electricity consumption optimization.
Keywords: Time of use tariff, critical peak pricing tariff, real time pricing tariff systems, sensors, smart-metering. |
3. Data integration approaches using ETL (p. 19-27)Alexandra Maria Ioana FLOREA, University of Economic Studies, Bucharest, RomaniaVlad DIACONITA, University of Economic Studies, Bucharest, Romania Ramona BOLOGA, University of Economic Studies, Bucharest, Romania |
|
Traditional data warehouses and ETL tools have been slowly pushed to expand their limits as big data has become a more and more prominent actor on the analytics stage. This paper analyzes and compares the features of Pentaho Data Integration and Oracle Data Integrator, two of the main data integration platforms. Such tools are relevant in the context of the evolution of the analytics field, which is expanding from classical business intelligence activities to the use and analysis of big data.
Keywords: business intelligence, data warehouse, big data, ETL. |
4. Big Data, the perfect instrument to study today's consumer behavior (p. 28-42)Cristina STOICESCU, University of Economic Studies, Bucharest, Romania |
|
Consumer behavior study is a new, interdisciplinary and emerging science, developed in the 1960s. Its main sources of information come from economics, psychology, sociology, anthropology and artificial intelligence. If a century ago, most people were living in small towns, with limited possibilities to leave their community, and few ways to satisfy their needs, now, due to the accelerated evolution of technology and the radical change of life style, consumers begin to have increasingly diverse needs. At the same time the instruments used to study their behavior have evolved, and today databases are included in consumer behavior research. Throughout time many models were developed, first in order to analyze, and later in order to predict the consumer behavior. As a result, the concept of Big Data developed, and by applying it now, companies are trying to understand and predict the behavior of their consumers.
Keywords: Big Data, consumer behavior, consumer experience, machine learning. |