Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/13420
Title: Effort Prediction With Limited Data: a Case Study for Data Warehouse Projects
Authors: Unlu, Huseyin
Yildiz, Ali
Demirors, Onur
Keywords: Data Warehouse
Size Measurement
Effort Estimation
Cosmic
Iso/Iec 19761
Publisher: IEEE
Abstract: Organizations may create a sustainable competitive advantage against competitors by using data warehouse systems with which they can assess the current status of their operations at any moment. They can analyze trends and connections using up-to-date data. However, data warehouse projects tend to fail more often than other projects as it can be tough to estimate the effort required to build a data warehouse system. Functional size measurement is one of the methods used as an input for estimating the amount of work in a software project. In this study, we formed a measurement basis for DWH projects in an organization based on the COSMIC Functional Size Measurement Method. We mapped COSMIC rules on two different architectures used for DWH projects in the organization and measured the size of the projects. We calculated the productivity of the projects and compared them with the organization's previous projects and DWH projects in the ISBSG repository. We could not create an organization-wide effort estimation model as we had a limited number of projects. As an alternative, we evaluated the success of effort estimation using DWH projects in the ISBSG repository. We also reported the challenges we faced during the size measurement process.
URI: https://doi.org/10.1109/SEAA56994.2022.00044
ISBN: 9781665461528
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
13420.pdf433.71 kBAdobe PDFView/Open
Show full item record



CORE Recommender

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.