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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Agile vs Hyper Agile : en studie av agilitet i metoder för datamodellering

Svensson, Martin January 2012 (has links)
Inom utvecklingen av de flesta typer av datorsystem används datormodeller för att strukturera lagringen och användningen av data. Likaså finns det flera olika datamodelleringsmetoder att välja bland för detta ändamål. I samarbete med ett företag har en fallstudie genomförts med syfte att undersöka hur agiliteten i två av dessa metoder påverkar utvecklingen av ett Data Warehouse (DW).  De två datamodelleringsmetoder som undersökts är Data Vaulting och Hyper Agility och arbetet har fokuserat på att undersöka skillnaderna mellan dessa när det gäller mängden ETL-kod som måste skrivas, funktionaliteten i datatransformationerna, möjligheten till att uppdatera systemstrukturen samt den totala kostnaden för utvecklingen av DW-lösningen. Inom ramen för fallstudien har en litteraturstudie genomförts och kombinerats med material från sex intervjuer, där respondenterna varit konsulter såväl som företagsrepresentanter.   Resultaten av fallstudien visar att respektive metods agilitet har en stor påverkan på den kod som utvecklas. Ju högre agilitet metoden har desto mindre kod, tid och andra resurser som krävs. Dock medför även en förhöjd agilitet större komplexitet samt eventuell risk för ett misslyckat utvecklingsprojekt.
2

A comparison of the impact of data vault and dimensional modelling on data warehouse performance and maintenance / Marius van Schalkwyk

Van Schalkwyk, Marius January 2014 (has links)
This study compares the impact of dimensional modelling and data vault modelling on the performance and maintenance effort of data warehouses. Dimensional modelling is a data warehouse modelling technique pioneered by Ralph Kimball in the 1980s that is much more effective at querying large volumes of data in relational databases than third normal form data models. Data vault modelling is a relatively new modelling technique for data warehouses that, according to its creator Dan Linstedt, was created in order to address the weaknesses of dimensional modelling. To date, no scientific comparison between the two modelling techniques have been conducted. A scientific comparison was achieved in this study, through the implementation of several experiments. The experiments compared the data warehouse implementations based on dimensional modelling techniques with data warehouse implementations based on data vault modelling techniques in terms of load performance, query performance, storage requirements, and flexibility to business requirements changes. An analysis of the results of each of the experiments indicated that the data vault model outperformed the dimensional model in terms of load performance and flexibility. However, the dimensional model required less storage space than the data vault model. With regards to query performance, no statistically significant differences existed between the two modelling techniques. / MSc (Computer Science), North-West University, Potchefstroom Campus, 2014
3

A comparison of the impact of data vault and dimensional modelling on data warehouse performance and maintenance / Marius van Schalkwyk

Van Schalkwyk, Marius January 2014 (has links)
This study compares the impact of dimensional modelling and data vault modelling on the performance and maintenance effort of data warehouses. Dimensional modelling is a data warehouse modelling technique pioneered by Ralph Kimball in the 1980s that is much more effective at querying large volumes of data in relational databases than third normal form data models. Data vault modelling is a relatively new modelling technique for data warehouses that, according to its creator Dan Linstedt, was created in order to address the weaknesses of dimensional modelling. To date, no scientific comparison between the two modelling techniques have been conducted. A scientific comparison was achieved in this study, through the implementation of several experiments. The experiments compared the data warehouse implementations based on dimensional modelling techniques with data warehouse implementations based on data vault modelling techniques in terms of load performance, query performance, storage requirements, and flexibility to business requirements changes. An analysis of the results of each of the experiments indicated that the data vault model outperformed the dimensional model in terms of load performance and flexibility. However, the dimensional model required less storage space than the data vault model. With regards to query performance, no statistically significant differences existed between the two modelling techniques. / MSc (Computer Science), North-West University, Potchefstroom Campus, 2014

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