1,721,017 research outputs found
System Architecture for Approximate Query Processing
Full text linkDecision 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
Semantic Data Analysis using Bitmap Indices
No full textAbstract: - The use of bitmap indexes for representing analytical views of user’s data is presented. This approach differs from the conventional definition and use of bitmap indexes in that they are defined not only to index different domain attribute values, but also for pre-computing any legal relational algebra query expression of the user for the analytic purposes. The paper illustrates the meaning of the analytical bitmaps and their application for solving problems of data integration and logical association between data. Furthermore, a fast access algorithm to enquire analytic bitmaps is presented
Extended Semantics of bitmaps for Data Analysis
No full textAbstract: - 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
Metadata for Approximate Query Answering Systems
Full text linkIn business intelligence systems, data warehouse metadata management and representation are getting more and more attention
by vendors and designers. The standard language for the data warehouse metadata representation is the Common Warehouse
Metamodel. However, business intelligence systems include also approximate query answering systems, since these software tools
provide fast responses for decisionmaking on the basis of approximate query processing. Currently, the standard meta-model does
not allow to represent the metadata needed by approximate query answering systems. In this paper, we propose an extension of
the standard metamodel, in order to define the metadata to be used in online approximate analytical processing. These metadata
have been successfully adopted in ADAP, a web-based approximate query answering system that creates and uses statistical data
profiles
Evaluation of Business Intelligence Systems
No full textBusiness Intelligence is an activity based on a set of processes and software tools. Its aim is to
support the decisional making phase, by extracting information from synthetical data. As the success of
such an activity depends on the effectiveness of several business processes and the correct integration
of independent software tools, nowadays standardization is strongly needed, in order to define a
methodology to obtain high-quality information, really useful for the improvement of the business
processes of an Information System. In this context, our study focuses on a framework that
encapsulates current emerging criteria to evaluate every facet of Business Intelligence systems. In our
case study, we tested the criteria to evaluate Business Intelligence platforms, by developing a real
OLAP application in an Academic Information System
Estimation of Database Unique Values
No full textAbstract: - Counts of database unique values are crucial information in query optimization. Estimating the
number of the distinct values occurs frequently in database queries, due to its importance in selecting query
plans. We present a nonparametric method for estimating the database distincts, and, then, the number of distinct
values. The method computes few parameters which describe the distribution of distances of distinct values in
the attribute value ranges. Tests have been carried out that also show the useful applicability of the method to
estimate equi-join selectivity factors
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