Techniques for semi-automatic generation of data cubes from star-schemas

The aim of this thesis is to investigate techniques to better automate the process of generating data cubes from star- or snowflake schemas. The company Trimma builds cubes manually today, but we will investigate doing this more efficiently. We will select two basic approaches and implement them in...

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Main Author: Hinnerson, Mattias
Format: Others
Language:English
Published: Umeå universitet, Institutionen för datavetenskap 2017
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-130648
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spelling ndltd-UPSALLA1-oai-DiVA.org-umu-1306482017-01-28T05:15:39ZTechniques for semi-automatic generation of data cubes from star-schemasengHinnerson, MattiasUmeå universitet, Institutionen för datavetenskap2017The aim of this thesis is to investigate techniques to better automate the process of generating data cubes from star- or snowflake schemas. The company Trimma builds cubes manually today, but we will investigate doing this more efficiently. We will select two basic approaches and implement them in Prototype A and Prototype B. Prototype A is a direct method that communicates directly with a database server. Prototype B is an indirect method that creates configuration files that can, later on, get loaded onto a database server. We evaluate the two prototypes over a star schema and a snowflake schema case provided by Trimma. The evaluation criteria include completeness, usability, documentation and support, maintainability, license costs, and development speed. Our evaluation indicates that Prototype A is generally outperforming Prototype B and that prototype A is arguably performing better than the manual method current employed by Trimma. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-130648UMNAD ; 1090application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
description The aim of this thesis is to investigate techniques to better automate the process of generating data cubes from star- or snowflake schemas. The company Trimma builds cubes manually today, but we will investigate doing this more efficiently. We will select two basic approaches and implement them in Prototype A and Prototype B. Prototype A is a direct method that communicates directly with a database server. Prototype B is an indirect method that creates configuration files that can, later on, get loaded onto a database server. We evaluate the two prototypes over a star schema and a snowflake schema case provided by Trimma. The evaluation criteria include completeness, usability, documentation and support, maintainability, license costs, and development speed. Our evaluation indicates that Prototype A is generally outperforming Prototype B and that prototype A is arguably performing better than the manual method current employed by Trimma.
author Hinnerson, Mattias
spellingShingle Hinnerson, Mattias
Techniques for semi-automatic generation of data cubes from star-schemas
author_facet Hinnerson, Mattias
author_sort Hinnerson, Mattias
title Techniques for semi-automatic generation of data cubes from star-schemas
title_short Techniques for semi-automatic generation of data cubes from star-schemas
title_full Techniques for semi-automatic generation of data cubes from star-schemas
title_fullStr Techniques for semi-automatic generation of data cubes from star-schemas
title_full_unstemmed Techniques for semi-automatic generation of data cubes from star-schemas
title_sort techniques for semi-automatic generation of data cubes from star-schemas
publisher Umeå universitet, Institutionen för datavetenskap
publishDate 2017
url http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-130648
work_keys_str_mv AT hinnersonmattias techniquesforsemiautomaticgenerationofdatacubesfromstarschemas
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