Database Systems Journal

ISSN 2069 - 3230

The journal is published under the sponsorship of
The Bucharest University of Economic Studies
and it is produced by the university's own publishing division,
The Bucharest University of Economic Studies Publishing House

Database Systems Journal, Vol. III, Issue 4/2012
Issue Topic: Analytics and Business Intelligence

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1. Perspectives on Big Data and Big Data Analytics (p. 3-14)
Elena Geanina ULARU, University of Economic Studies, Bucharest, Romania
Florina Camelia PUICAN, University of Economic Studies, Bucharest, Romania
Anca APOSTU, University of Economic Studies, Bucharest, Romania
Manole VELICANU, University of Economic Studies, Bucharest, Romania
Nowadays companies are starting to realize the importance of using more data in order to support decision for their strategies. It was said and proved through study cases that “More data usually beats better algorithms”. With this statement companies started to realize that they can chose to invest more in processing larger sets of data rather than investing in expensive algorithms. The large quantity of data is better used as a whole because of the possible correlations on a larger amount, correlations that can never be found if the data is analyzed on separate sets or on a smaller set. A larger amount of data gives a better output but also working with it can become a challenge due to processing limitations. This article intends to define the concept of Big Data and stress the importance of Big Data Analytics.
Keywords: Big Data, Big Data Analytics, Database, Internet, Hadoop project.
2. Real-Time Business Intelligence for the Utilities Industry (p. 15-24)
Janina POPEANGA, University of Economic Studies, Bucharest, Romania
Ion LUNGU, University of Economic Studies, Bucharest, Romania
In today’s competitive environment with rapid innovation in smart metering and smart grids, there is an increased need for real-time business intelligence (RTBI) in the utilities industry. Giving the fact that this industry is an environment where decisions are time sensitive, RTBI solutions will help utilities improve customer experiences and operational efficiencies. The focus of this paper is on the importance of real-time business intelligence (RTBI) in the utilities industry, outlining our vision of real-time business intelligence for this industry. Besides the analysis in this area, the article presents as a case study the Oracle Business Intelligence solution for utilities.
Keywords: Real-time business intelligence, data latency, external real-time data cache, real-time data warehouse, Oracle Utilities Business Intelligence.
3. A Framework for Automated Database Tuning Using Dynamic SGA Parameters and Basic Operating System Utilities (p. 25-32)
Hitesh KUMAR SHARMA, University of Petroleum and Energy Studies, India
Aditya SHASTRI, Banasthali University, Rajasthan, India
Ranjit BISWAS, Department of Computer Science, Hamdard University, India
In present scenario the manual work (Done by Human) cost more to an organization than the automatic work ( Done by Machine)and the ratio is increasing day by day as per the tremendous increment in Machine (Hardware + Software) Intelligence. We are moving towards the world where the Machines will be able to perform better than today by their own intelligence. They will adjust themselves as per the customer’s performance need. But to make this dream true, lots of human efforts (Theoretical and Practical) are needed to increase the capability of Machines to take their own decision and make the future free from manual work and reduce the working cost. Our life is covered with the different types of systems working around. The information system is one of them. All businesses are having the base by this system. So there is the most preference job of the IT researcher to make the Information system self-Manageable. The Development of well-established frameworks are needed to made them Auto-tuned is the basic need of the current business. The DBMS vendors are also providing the Auto-Tune packages with their DBMS Application. But they charge for these Auto-Tune packages. This extra cost of packages can be eliminated by using some basic Operating system utilities (e.g. VB Script, Task Scheduler, Batch Files, and Graphical Utility etc.). We have designed a working framework for Automatic Tuning of DBMS by using the Basic Utilities of Operating System (e.g. Windows) .These utilities will collect the statistics of SGA dynamic Parameters. The Framework will automatically analyze these SGA Parameter statistics and give suggestions fordiagnose the problem. In this paper we have presented that framework with practical Implementation.
Keywords: SGA, SGA Dynamic Parameters, Database Tuning, DBA, Automated Tuning, TOC.
4. A Multidimensional View Proposal of the Data Collected Through a Questionnaire. Associated Data Mart Deployment Framework (p. 33-46)
Mihaela I.MUNTEAN, Department of Business Information Systems, Faculty of Business Administration, West University of Timisoara, Timisoara, Romania
Diana TARNAVEANU, Department of Business Information Systems, Faculty of Business Administration, West University of Timisoara, Timisoara, Romania
Beyond the traditional data analysis approaches based on SPSS (or similar statistical software tools), an alternative demarche will be subject of our debate. Performant data analysis can be completed based on a multidimensional view of the collected data. This implies an additional data mart powered with information obtained through an ETL process from the collected data. Measures and dimensions will facilitate a subject-oriented, time-based analysis. The theoretical approach framework for deploying the data mart will ground a multidimensional analysis on „how the different respondents answered to the questions included into the questionnaire?“. In addition, a study case was proposed, a questionnaire built and different analyses presented.
Keywords: Multidimensional model, questionnaire, data mart, ETL, data analysis.
5. Multi-level and Multi-component Bitmap Encoding for Efficient Search Operations (p. 47-60)
Madhu BHAN, Department of Computer Applications, M.S.Ramaiah Institute of Technology, India
RAJANIKANTH K, Department of Computer Applications, M.S.Ramaiah Institute of Technology, India
Suresh KUMAR T.V, Visvesvaraya Technological University, India
The growing interest in data warehousing for decision makers is becoming more and more crucial to make faster and efficient decisions. On-line decision needs short response times. Many indexing techniques have been created to achieve this goal in read only environments. Indexing technique that has attracted attention in multidimensional databases is Bitmap Indexing. The paper discusses the various existing bitmap indexing techniques along with their performance characteristics. The paper proposes two new bitmap indexing techniques in the class of multi-level and multi-component encoding schemes and prove that the two techniques have better space–time performance than some of the existing techniques used for range queries. We provide an analytical model for comparing the performance of our proposed encoding schemes with that of the existing ones.
Keywords: Bitmap encoding, Datawarehouse, multi-level indexing, multi-component indexing, On-Line Analytical Processing.
6. Grid and Data Analyzing and Security (p. 61-72)
Fatemeh SHOKRI, Computer Engineering Department, Mazandaran Institute of Technology, Mazandaran, Iran
This paper examines the importance of secure structures in the process of analyzing and distributing information with aid of Grid-based technologies. The advent of distributed network has provided many practical opportunities for detecting and recording the time of events, and made efforts to identify the events and solve problems of storing information such as being up-to-date and documented. In this regard, the data distribution systems in a network environment should be accurate. As a consequence, a series of continuous and updated data must be at hand. In this case, Grid is the best answer to use data and resource of organizations by common processing.
Keywords: Grid Computing, Secure Structure, Common Processing.
7. Semi-Distributed Vacuuming Model on Temporal Database (SDVMT) (p. 73-79)
Mohammad Shabanali FAMI, Islamic Azad University, Iran
Elham Shabanali FAMI, Isfahan University of Technology, Iran
Mohammad Ali MONTAZERI, Isfahan University of Technology, Iran
Mohammad Taghi ISAAI, Sharif University of Technology, Iran
Temporal database is one of the most common types of databases. Portfolio management, accounting, storage, treatment management systems, aerology systems and scheduling are applications which their data have time references. Temporal nature of data and increasing size of temporal databases due to non-removal data requires presenting a solution to overcome this limitation. In this research, firstly the current model of vacuuming systems are simulated and analyzed. Then the proposed model introduced for vacuuming systems using distribution concepts. This model is simulated in the same conditions with current model. Using experimental results, advantages and disadvantages of both models were investigated. The proposed model is more capable than the current model in answering temporal queries. Its response time to temporal queries is less than the current model. But the proposed model's cost is more than the current model. Considering the possibility of idle resources usage in organizations, these costs can be ignored along with optimize usage of facilities.
Keywords: Vacuuming, Multiclass queuing model, Schema versioning, temporal database.