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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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 |
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English |
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Others
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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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1718410625765343232 |