Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems

Data warehouses are based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels (using roll-up and drill-down functions). Therefore, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge, which (1) has a complex structure and dynamics and (2) is highly contextual. In order to account for the characteristics of this knowledge, we propose to represent it with objects (UML class diagrams) and rules in Production Rule Representation (PRR) language. Static aggregation knowledge is represented in the class diagrams, while rules represent the dynamics (i.e. how aggregation may be performed depending on context). We present the class diagrams, and a typology and examples of associated rules. We argue that this representation of aggregation knowledge allows an early modeling of user requirements in a data warehouse project.Aggregation; Conceptual Multidimensional Model; Data Warehouse; On-line Analytical Processing (OLAP); Production Rule; UML

On-line analytical processing

On-line analytical processing (OLAP) describes an approach to decision support, which aims to extract knowledge from a data warehouse, or more specifically, from data marts. Its main idea is providing navigation through data to non-expert users, so that they are able to interactively generate ad hoc queries without the intervention of IT professionals. This name was introduced in contrast to on-line transactional processing (OLTP), so that it reflected the different requirements and characteristics between these classes of uses. The concept falls in the area of business intelligence.Peer ReviewedPostprint (author's final draft

Designing OLAP Cubes: A Teaching Case

This teaching case models the process used to create a “proof of concept” data warehouse and On-line Analytical Processing (OLAP) Cube for admissions at small, private, Midwestern university. Students will use test data to design Star Schemas and create OLAP cubes to show how they could be used for data mining purposes. This case attempts to build an understanding of the design and use of data warehouses and OLAP cubes within a larger data mining course

A Simpler Approach to Set Comparison Queries in SQL

The current specification of the SQL standard fails to support users adequately in formulating complex queries involving set comparison that tend to arise in on-line analytical processing (OLAP) situations. Such queries must be formulated using correlated subqueries and the NOT EXISTS function which present an overwhelming challenge to both casual as well as everyday SQL users. This paper presents a simpler approach for teaching users how to formulate in SQL complex set comparison queries encountered in ad-hoc decision making scenarios

XWeB: the XML Warehouse Benchmark

With the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of benchmarks. However, decision support benchmarks do not currently support XML features. In this paper, we introduce the XML Warehouse Benchmark (XWeB), which aims at filling this gap. XWeB derives from the relational decision support benchmark TPC-H. It is mainly composed of a test data warehouse that is based on a unified reference model for XML warehouses and that features XML-specific structures, and its associate XQuery decision support workload. XWeB's usage is illustrated by experiments on several XML database management systems

On-Line Analytical Processing (OLAP) : Entscheidungsunterstützung von Führungskräften durch mehrdimensionale Datenbanksysteme

Seit einigen Jahren wird die Eignung von mehrdimensionalen Datenbanksystemen (OLAP) für die Analyseanforderungen von Führungskräften diskutiert. In dem Beitrag wird das OLAP-Konzept vorgestellt und im Hinblick auf die Unterstützung von Führungsentscheidungen untersucht

On-Line Analytical Processing Accounting: Potentials, Application, and Design Methodology

Most software vendors and business consultants agree that On-Line Analytical Processing (OLAP) tools are needed to derive useful decision support from accounting transaction data. But business solutions can not be created just by installing and integrating some tool(s). To support a selection from the growing number of tools, potentials and applications of OLAP for accounting must be clarified. Moreover, a methodology for designing OLAP applications is needed. Being aware that all research in this brand-new field is still in progress, we address these problems in this paper