Atti del convegno

Data Warehouse with Big Data Technology for Higher Education

This research intends to shed some light on the influence of culture on the learners understanding of culture specific jokes. For this purpose, the responses of the volunteer students of first year master of English at Constantine University have been collected. The research work is mainly concerned with finding whether the high exposure to the foreign language culture has anything to do with the learner’s level of understanding of jokes. Both the quantitative and qualitative analysis indicated that there is an association between the learners’ level of understanding of the jokes and their exposure to culture. Despite the limited scope of this study, the research findings revealed interesting implications on research to the teaching of the foreign culture to students at university level.

People's Democratic Republic of Algeria Ministry of Higher Education and Scientific Research

This paper outlines a general methodological framework for DW design and discusses the relationships between different steps and how to carry them out based on the difference between data warehouse and operational system.

A Methodological Framework for Data Warehouse Design

............................................................................................................... iv TIIVISTELMÄ ............................................................................................................. v ACKNOWLEDGEMENTS ......................................................................................... vi TABLE OF CONTENTS ............................................................................................. ix LIST OF FIGURES ................................................................................................... xiii LIST OF TABLES ...................................................................................................... xv PART I: INTRODUCTION

Social Media Changing the Competitive Intelligence Process: Elicitation of Employees’ Competitive Knowledge

There are several benefits that can be reached by developing an academic data warehouse as providing a centralized source of information accessible across different academic units to quickly analyze problems and get satisfactory solutions, supplying the data necessary for developing the Institution's strategic plan, and enabling administrator to make better business decisions based on historical data available in legacy databases. The paper describes the architecture of an academic data warehouse. Examples of analytic reporting are also reported.

http://www.wseas.us/e-library/conferences/2007athensel/papers/564-091.pdf

An academic data warehouse

The current lack of a standard methodology for data warehouse design has led to have many possible lifecycles. In some of them, the validation of the data warehouse conceptual schema is a specific process that precedes the translation of such a schema into a logical one. This activity must ensure that the data warehouse to be implemented effectively allows all the analytical queries to be executed correctly. To accomplish this, the validation process takes the preliminary workload into account, that is, a set of queries defined from user requirements to obtain the typical information the users are interested in. The methodologies that perform such a validation process define some guidelines that must be manually executed by an expert. In this paper, we introduce a logic program to automate this activity, by checking a set of predefined issues with an inferential engine.

Logic programming for data warehouse conceptual schema validation

The Dimensional Fact Model is a conceptual model that allows to design the multidimensional schema of a data warehouse. Its methodology is based on the (re)modelling of the schema of a relational database; such a schema is represented by a tree, and the (re)modelling consists of the traditional operations on graphs (as prune, graft, adding child, change parent, …). The tree is generated automatically by an algorithm, starting from the logical schema of a relational database. Nowadays, this algorithm is not able to manage many-to-many relationships, and then, it stops the tree creation when it meets this kind of relationships. In this work, we propose a novel methodology, able to overcome this algorithmic limit, via the declarative approach of the logical programming.

Dimensional fact model extension via predicate calculus

The Information Technology is an essential support in the decisional process to improve manager' phenomena knowledge, that is often approximate and ill-structured. Tools underlying decision support systems (as OLAP systems, data mining, and data warehouses) have a central role in enterprise information systems. In this paper, we present the design and the implementation of a national data warehouse.

http://www.wseas.us/e-library/conferences/2006madrid/papers/512-263.pdf

Design and implementation of a national data warehouse

The paper examines some common platforms supporting Business Intelligence activities in order to state evaluation criteria for the system choice. The evaluation considers a software measurement method based on the analysis of the functional complexity of the platforms. The study has been performed on an academic warehouse that uses historical data available in legacy databases. Experimental results are reported which show the advantages and the drawbacks of each considered system.

http://www.wseas.us/e-library/conferences/2008/uk/AIKED/AIKED-85.pdf

Carlo Dell'Aquila

Papers

An academic data warehouse

Logic programming for data warehouse conceptual schema validation

Dimensional fact model extension via predicate calculus

Design and implementation of a national data warehouse

Evaluating business intelligence platforms: a case study