Database Systems Journal, Vol. V, Issue 4/2014
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1. 'Shared-Nothing' Cloud Data Warehouse Architecture (p. 3-11)Janina POPEANGA, University of Economic Studies, Bucharest, Romania |
Energy management systems from Romania do not have the capabilities of energy specific management due to lack of technology for real-time monitoring. As was the case in many other countries, the advent of smart metering technology will increase the level of energy data significantly. Therefore, the purpose of this paper is to present solutions that need to be taken to solve problems linked with the increasing amount of data recorded by sensors.
For a better demonstration of theoretical elements exposed, we considered a data warehouse specific to utility companies. Section 2 of this article defines the three widely used parallel data warehouse architectures, while in Section 3 we clarify what architecture is suited to develop a data warehouse in the cloud. In the last part we transposed our tables in a "shared-nothing" architecture, trying to analyze queries performance. Keywords: Shared-nothing architecture, Data Warehouse, Replication, Distribution, Cloud. |
2. Informatics Solutions for Prosumers connected to Smart Grids (p. 12-20)Simona Vasilica OPREA, University of Economic Studies, Bucharest, Romania |
This paper gives a brief overview about electricity consumption optimization based on consumption profiles of electricity prosumers that are connected to smart grids. The main object of this approach is identification of informatics solutions for electricity consumption optimization in order to decrease electricity bill. In this way, larger scale integration of renewable energy sources is allowed therefore entire society will gain benefits. This paper describes the main objectives of such informatics system and stages for its implementation. The system will analyze the specific profile and behavior of each electricity consumer or prosumer, automatically assist him to make right decisions and offer optimal advice for usage of controllable and non-controllable appliances. It will serve, based on big data transfer from electricity consumers or prosumers, as a powerful tool for grid operators that will be able to better plan their resources.
Keywords: smart metering, advanced tariffs system, big data, electricity consumption optimization, prosumer, renewable energy sources. |
3. Reshaping Smart Businesses with Cloud Database Solutions (p. 21-38)Bogdan NEDELCU, University of Economic Studies, Bucharest, RomaniaAndreea Maria IONESCU, University of Economic Studies, Bucharest, Romania Ana Maria IONESCU, University of Economic Studies, Bucharest, Romania Alexandru George VASILE, University of Economic Studies, Bucharest, Romania |
The aim of this article is to show the importance of Big Data and its growing influence on companies. We can also see how much are the companies willing to invest in big data and how much are they currently gaining from their big data. In this big data era, there is a fiercely competition between the companies and the technologies they use when building their strategies. There are almost no boundaries when it comes to the possibilities and facilities some databases can offer. However, the most challenging part lays in the development of efficient solutions - where and when to take the right decision, which cloud service is the most accurate being given a certain scenario, what database is suitable for the business taking in consideration the data types. These are just a few aspects which will be dealt with in the following chapters as well as exemplifications of the most accurate cloud services (e.g. NoSQL databases) used by business leaders nowadays.
Keywords: Smart business, cloud database, cloud solutions, NoSQL databases, weaknesses, key-value databases, Riak, columnar databases, Hbase, document-oriented databases, MongoDB, graph databases, Neo4j, cloud services. |
4. Data Model for SIPAMER Prototype (p. 39-48)Adela BARA, University of Economic Studies, Bucharest, RomaniaAnca ANDREESCU, University of Economic Studies, Bucharest, Romania |
The article presents the data model of the decision support systems in energy field and the future work plan for design development of cloud service information system for integration and knowledge management based in renewable energy. The research is part of SIPAMER project, financed by NASR agency.
Keywords: decision support systems, XML, data integration, data model, renewable energy sources. |
5. Cloud Computing and Business Intelligence (p. 49-58)Alexandru Adrian TOLE, Romanian - American University, Bucharest, Romania |
The complexity of data resulting from business process is becoming overwhelming for the systems that don't use shared resources. Many aspects of the business process must be recorded and analysed in a short period of time with no errors at all. In order to obtain these results, so that management and other departments know what their next decision/job will be, there must be a continuous exchange and processing of information.
"Cloud Computing" is the solution to overcome the problem of processing large amounts of data. By using this technology organizations have the benefit of using shared resources from various systems that are able to face large amount of data processing. This benefits does not only resume to a high performance system but also the costs of using such architecture are much lower. Keywords: Cloud Computing, Business Intelligence, shared resources, hardware architecture, SaaS, PaaS, IaaS. |
6. Master program Databases - Support for Business (BDSA). Development competition BDSA - Oracle Academy 2015 (p. 59) |