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Prototype of a Tool for Managing and Executing OLAP Patterns

  • Michael Moritz

Research output: ThesisMaster's / Diploma thesis

Abstract

The OLAP pattern approach allows to document generic strategies for composing OLAP queries to satisfy specific types of information needs. Such OLAP patterns can document best practices for the (re)use within and across domains or organizations in future query compositions. The necessary steps to define and use an OLAP pattern are specified by the OLAP pattern approach. The definition process describes how a new pattern can be defined, while the usage process describes how an OLAP pattern can be adapted to a specific analysis situation. In this thesis a repository to support these processes is prototypically implemented. This repository for OLAP patterns should serve as a central access point within organizations and support the definition, storage and usage of OLAP patterns. Communication with users is done by entering commands that follow a predefined language for defining and using OLAP patterns. The repository also supports the definition of multidimensional data models and business terms based on them, which serve as the basis for the OLAP pattern approach. A multidimensional data model allows to conceptually map a concrete data warehouse of an organization, while business terms map the necessary business vocabulary to describe information needs. Furthermore, the repository provides structuring and access options to logically structure OLAP patterns, business terms and multidimensional models and to search for them. Finally, the repository supports the adaptation of OLAP patterns to specific information needs and the execution of fully customized OLAP patterns for the purpose of generating the required OLAP query.
Original languageEnglish
Supervisors/Reviewers
  • Schrefl, Michael, Supervisor
  • Kovacic, Ilko, Co-supervisor
Publication statusPublished - Oct 2020

Fields of science

  • 102 Computer Sciences
  • 102010 Database systems
  • 102015 Information systems
  • 102016 IT security
  • 102025 Distributed systems
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 102035 Data science
  • 502050 Business informatics
  • 503008 E-learning

JKU Focus areas

  • Digital Transformation

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