system architecture for approximate query processing

Decision making is an activity that addresses the problem of extracting knowledge and information from data stored in data warehouses, in order to improve the business processes of information systems. Usually, decision making is based on On-Line Analytical Processing, data mining, or approximate query processing. In the last case, answers to analytical queries are provided in a fast manner, although affected with a small percentage of error. In the paper, we present the architecture of an approximate query answering system. Then, we illustrate our ADAP (Analytical Data Profile) system, which is based on an engine able to provide fast responses to the main statistical functions by using orthogonal polynomials series to approximate the data distribution of multi­dimensional relations. Moreover, several experimental results to measure the approximation error are shown and the response-time to analytical queries is reported.</p

An Analytic Approach to Statistical Databases

Abstract. In the commonly adopted data models (as ins entity-relationship data model 111, for example) an attribute is a mapping between an en-tity set or a relationship set and a value set. The intension of a mapping property is given im-plicitly or explicitly in the data models, but the extension can be generally represented by the set I&lt;entity,value&gt;), as in the relational model. We propose an alternative data model for statisti cal databases, in which an attribute is represen-ted by its analytic properties (the distribution function of the values of the attribute). These analytic properties are described by a set of pa-rameters,which we call the canonica2 coefficients of the attribute. The canonical coefficients can be used to solve the usual statistical queries with no access to the data. In particular, we pre sent: 1) the methods for computing and updating the canonical coefficients, 2) the use of the ca-nonical coefficients for solving the main statis-tical queries, also in distributed statistical database environments. Besides, an application of such parameters to the query decomposition in distributed database environments is discussed

Teaching Data Bases with a Learning Tool

Abstract: - A system that supports learning activities on data base management systems for the degree course in computer science is presented. After an accurate analysis of main open source tools, the system has been developed using ATutor, a freeware and multiplatform Learning Component Management System developed at the University of Toronto. The learning environment contains several courses, but our attention points out on the data base course. The course structure and evaluation criteria for system usability are discussed

Extended Semantics of bitmaps for Data Analysis

Abstract: - The contribution of this paper relates to the ability of bitmap indices to support OLAP-oriented queries and analyses. On one hand, the Bitmap index access method improves the serial data access performance. On the other hand, the Bitmap index semantics and use allow one to include the definition and management of complex classes dynamically investigated for analytic purposes. In this novel approach, bitmaps are defined at a higher abstraction level than the traditional indices and bitmaps. In fact, they allow the analytic or decisional user to also categorize objects which satisfy any legal relational query

Design of an e-learning Environment for Teaching Databases and Information Systems

Abstract: - We present a system that provides an e-learning environment in the database and information system fields. The system has been designed to support different teaching needs deriving not only from the computer science degree, but also from others University degrees that require database skills. For this purpose, it has been developed a repository of didactic modules on database and advanced database topics organized to support the different needs of potential students

Host Fingerprinting for Web Servers Authentication

Fingerprinting is a biometric technique for computing a unique profile associated to a physical person for authentication purpose. It has been successfully applied also to software entities by using hash functions for integrity checking after downloading. In the paper, we propose a fingerprinting algorithm to identify a machine during a client-server authentication process. In detail, this host identifier can be used for connecting to a database server without using an account storing a plain-text password. After the presentation of experimental results, we show some real scenarios where this solution can be applied