This paper proposes an extension of Datalog devoted to data manipulations in On-Line Analytical Processing (OLAP) systems. This language provides a declarative and concise way to specify the basic standard restructuring and summarizing operations on multidimensional cubes used in these systems. We define its model-theoretic semantics and an equivalent fixpoint semantics that leads to a naive evaluation procedure. We also illustrate its applicability to specify usefull more complex data manipulations arising in OLAP systems.

For being in this changed rapidly new economic era, network technology has brought significant reform for enterprise operational mode, human resource information system has developed with the advantage of information technology, and become a necessary manage instrument gradually, adopt systematic and statistical analyze mode, collocated to display with visional graphic table (such as analytic form or statistic sketch), let high-level and human resource chief be capable of scientific and specific policy assistant data. Data Warehouse is a new technology for data storage, within the data warehouse not only could compile data, even more proceed to decompose¡Bmerge and intersect in different range and layer, and then utilizing the function of On-Line Analytical Processing (OLAP) or Data Mining to obtain one step ahead of information, providing applicable message for policy maker. Therefore, in recent year, data warehouse has become the main data source of Decision Support System (DSS) gradually. This research attempts to establish a data warehouse fledgling model for human resource management, providing the basic requirement for rapidly inquire related statistic data for policy maker, and extract data from human manage information system data base, establish a related multiple dimension data model. And apply the technology of Data Warehouse and OLAP, via Internet, policy maker could depends on his requirement inquiring related statistic data elastically and rapidly, and enhance the quality and time effectiveness of decision. This research could establish the systematic benefits as below¡G ¢¹.Provide convenience to inquire data: via mouse proceed dragging action, rapidly and time effectively let user operate conveniently in data inquiring procedure. ¢º.Multi-dimensional analyze data: owing to OLAP could support multi-dimensional inquire, and makes different intersect analyze and variation comparison, could let the manager make decision reference material more explicitly. ¢».Obtain necessary information elastically: could depend on user¡¦s requirement, arbitrarily change dimension, obtain necessary information, increase user¡¦s inquiring elasticity. ¢¼.Via network medium access: establishing the base system by web-base, via network and browser could forward to inquire, enhance the system¡¦s mobility and convenience. ¢½.Function of data base examination: through OLAP statistic outcome, could reach examine database correctly and completely.

This thesis is written at the department of Business Studies at Uppsala University. The study addresses the differences in possibilities and difficulties of implementing business intelligence (BI)-systems among small IT-enterprises. BI-systems support enterprises in decision-making. To answer the aim of this thesis, theories regarding organizational factors determining a successful implementation of a BI-system were used. Theories regarding components of BI- systems, data warehouse (DW) and online analytical processing (OLAP) were also used. These components enable the decision-support provided by a BI-system. A qualitative study was performed, at four different IT-enterprises, to gather the empirical material. Interviews were performed with CEOs and additional employees at the enterprises. After the empirical material was gathered an analysis was performed to draw conclusion regarding the research topic. The study has concluded that there are differences in possibilities and difficulties of implementing BI-systems among small IT-enterprises. A difference among the enterprises is the perceived ability to finance an implementation. Another difference is in the managerial- and organizational support of an implementation, but also in the business need of using a BI- system in decision-making. There are also differences in how the enterprises use a DW. Not all enterprises benefits from the ability of a DW to manage complex and large amounts of data, neither from the advanced analysis performed by OLAP. The enterprises thus need to examine further if the use of a BI-system is beneficial and would be used successfully in their company.

[Truncated abstract] Many databases in scientific and business applications have grown exponentially in size in recent years. Accessing and using databases is no longer a specialized activity as more and more ordinary users without any specialized knowledge are trying to gain information from databases. Both expert and ordinary users face significant challenges in understanding the information stored in databases. The databases are so large in most cases that it is impossible to gain useful information by inspecting data tables, which are the most common form of storing data in relational databases. Visualization has emerged as one of the most important techniques for exploring data stored in large databases. Appropriate visualization techniques can reveal trends, correlations and associations in data that are very difficult to understand from a textual representation of the data. This thesis presents several new frameworks for data visualization and visual data mining. The first technique, VisEx, is useful for visual exploration of large multi-attribute datasets and especially for exploring the correlations among the attributes in such datasets. Most previous visualization techniques can display correlations among two or three attributes at a time without excessive screen clutter. ... Although many algorithms for mining association rules have been researched extensively, they do not incorporate users in the process and most of them generate a large number of association rules. It is quite often difficult for the user to analyze a large number of rules to identify a small subset of rules that is of importance to the user. In this thesis I present a framework for the user to interactively mine association rules visually. Another challenging task in data mining is to understand the correlations among the mined association rules. It is often difficult to identify a relevant subset of association rules from a large number of mined rules. A further contribution of this thesis is a simple framework in the VisAR system that allows the user to explore a large number of association rules visually. A variety of businesses have adopted new technologies for storing large amounts of data. Analysis of historical data quite often offers new insights into business processes that may increase productivity and profit. On-line analytical processing (OLAP) has become a powerful tool for business analysts to explore historical data. Effective visualization techniques are very important for supporting OLAP technology. A new technique for the visual exploration of OLAP data cubes is also presented in this thesis.

Univ., Diss.--Mannheim, 2008.

Submitted by Lucelia Lucena (lucelia.lucena@ufpe.br) on 2015-03-04T18:33:54Z No. of bitstreams: 2 DISSERTAÇÃO Ana Cecília Vital de Andrade.pdf: 4377501 bytes, checksum: 62069caff1753987554f40017f60aa10 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-04T18:33:54Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO Ana Cecília Vital de Andrade.pdf: 4377501 bytes, checksum: 62069caff1753987554f40017f60aa10 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2014-03-14 / SOLAP é uma tecnologia resultante da integração das ferramentas OLAP (Online Analytical Processing) e SIG (Sistemas de Informação Geográfica), cujo objetivo é proporcionar novas possibilidades de análises, uma vez que permite integrar processamento espacial (SIG) e processamento multidimensional-multinível (OLAP) (e.g., qual foi o total de produtos vendidos por loja, cliente, ano, semestre e mês para os clientes que residem até 1km da matriz?). Embora existam muitos trabalhos relacionados à SOLAP, poucos dão atenção à especificação do cliente SOLAP. Neste contexto, ressalta-se que a maioria dos trabalhos existentes apenas dá suporte à manipulação de uma única dimensão espacial e apresentam poucos (algumas vezes nenhum) detalhes sobre a arquitetura e/ou recursos visuais para especificar e sincronizar graficamente operações OLAP e SIG em um cliente SOLAP. Visando propor uma alternativa ao problema descrito, esta dissertação especifica e implementa uma arquitetura de software e uma interface gráfica para um cliente SOLAP Web, o qual visa especificar graficamente operações SOLAP sobre uma ou mais dimensões espaciais, bem como sobre temas externos ao cubo de dados. Como prova de conceito, foi realizado um exemplo de uso do cliente SOLAP construído, que testa a realização de operações SOLAP com as características citadas.

No description available.

Online Analytical Processing (OLAP) has become the de facto data analysis technology used in modern decision support systems. It has experienced tremendous growth, and is among the top priorities for enterprises. Open source systems have become an effective alternative to proprietary systems in terms of cost and function. The purpose of the study was to investigate the performance of two leading database storage engines in an open source OLAP environment. Despite recent upgrades in performance features for the InnoDB database engine, the MyISAM database engine is shown to outperform the InnoDB database engine under a standard benchmark. This result was demonstrated in tests that included concurrent user sessions as well as asynchronous user sessions using data sets ranging from 6GB to 12GB. Although MyISAM outperformed InnoDB in all test performed, InnoDB provides ACID compliant transaction technologies are beneficial in a hybrid OLAP/OLTP system.

When the terms “Data Warehousing” and “Online Analytical Processing” were coined in the 1990s by Kimball, Codd, and others, there was an obvious need for separating data and workload for operational transactional-style processing and decision-making implying complex analytical queries over large and historic data sets. Large data warehouse infrastructures have been set up to cope with the special requirements of analytical query answering for multiple reasons: For example, analytical thinking heavily relies on predefined navigation paths to guide the user through the data set and to provide different views on different aggregation levels.Multi-dimensional queries exploiting hierarchically structured dimensions lead to complex star queries at a relational backend, which could hardly be handled by classical relational systems. [Off: Introduction]

The subject of the thesis is the proof of concept of Business Intelligence (BI) implementation in the Communications service department from the Kapsch BusinessCom s.r.o. company. The aim of the work is developing a BI proof solution and consequently producing an output for the final users. The main outcome of the thesis is operating BI solutions used in practice. The solution was carried out using tools MS SQL Server 2008 R2 Management Studio, MS SQL Server 2008 R2 Business Intelligence Development studio and MS Excel 2007. The project analyses the data obtained from the ERP (Enterprise Resource Planning) database acquired from the MS Dynamics Navision system. Information on "Voice" projects from the Communications service department, which mainly focuses on the service of PBXs and similar products, are recorded in the project among others. A multidimensional analysis was carried out, data warehouse was designed, data pumps were created, OLAP (On-line Analytical Processing) block and output in the Microsoft Excel 2007 program were carried out during the project.